---------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/log_replication_ubiturnout.log
  log type:  text
 opened on:  29 May 2022, 14:35:09

. do "/Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/cps_dataclean.do"

. 
. *-----------------------------------------------------------------------------
. **                       Does a UBI affect voter turnout                   **
. **                     Produce Individual-Level Data File                   **
. *-----------------------------------------------------------------------------
. 
. *** Individual level data 
. 
. use "cps_00017.dta"

. 
. 
. gen fip=statefip

. label val fip

. label var fip "State (FIPS code)"

. 
. *no cpsidp for age<14 1976-82; only interested in voting hence delete all minors
. drop if age<18
(479,879 observations deleted)

. 
. gen t=.
(1,250,237 missing values generated)

. replace t=1 if year==1978
(104,870 real changes made)

. replace t=2 if year==1980
(123,591 real changes made)

. replace t=3 if year==1982
(112,372 real changes made)

. replace t=4 if year==1984
(110,115 real changes made)

. replace t=5 if year==1986
(108,410 real changes made)

. replace t=6 if year==1988
(102,945 real changes made)

. replace t=7 if year==1990
(109,569 real changes made)

. replace t=8 if year==1992
(106,497 real changes made)

. replace t=9 if year==1994
(102,197 real changes made)

. replace t=10 if year==1996
(90,054 real changes made)

. replace t=11 if year==1998
(90,400 real changes made)

. replace t=12 if year==2000
(89,217 real changes made)

. label var t "time"

. 
. gen id=.
(1,250,237 missing values generated)

. replace id=1 if fip==1
(17,570 real changes made)

. replace id=2 if fip==2
(16,269 real changes made)

. replace id=3 if fip==4
(15,620 real changes made)

. replace id=4 if fip==5
(16,073 real changes made)

. replace id=5 if fip==6
(98,564 real changes made)

. replace id=6 if fip==8
(16,914 real changes made)

. replace id=7 if fip==9
(13,682 real changes made)

. replace id=8 if fip==10
(12,052 real changes made)

. replace id=9 if fip==11
(11,406 real changes made)

. replace id=10 if fip==12
(53,364 real changes made)

. replace id=11 if fip==13
(20,085 real changes made)

. replace id=12 if fip==15
(12,545 real changes made)

. replace id=13 if fip==16
(16,091 real changes made)

. replace id=14 if fip==17
(50,400 real changes made)

. replace id=15 if fip==18
(18,955 real changes made)

. replace id=16 if fip==19
(17,279 real changes made)

. replace id=17 if fip==20
(16,089 real changes made)

. replace id=18 if fip==21
(16,442 real changes made)

. replace id=19 if fip==22
(15,718 real changes made)

. replace id=20 if fip==23
(14,066 real changes made)

. replace id=21 if fip==24
(16,110 real changes made)

. replace id=22 if fip==25
(39,200 real changes made)

. replace id=23 if fip==26
(47,556 real changes made)

. replace id=24 if fip==27
(17,539 real changes made)

. replace id=25 if fip==28
(16,639 real changes made)

. replace id=26 if fip==29
(17,543 real changes made)

. replace id=27 if fip==30
(17,086 real changes made)

. replace id=28 if fip==31
(15,939 real changes made)

. replace id=29 if fip==32
(14,029 real changes made)

. 
. replace id=30 if fip==33
(11,883 real changes made)

. replace id=31 if fip==34
(44,416 real changes made)

. replace id=32 if fip==35
(15,678 real changes made)

. replace id=33 if fip==36
(80,439 real changes made)

. replace id=34 if fip==37
(38,446 real changes made)

. replace id=35 if fip==38
(16,777 real changes made)

. replace id=36 if fip==39
(51,709 real changes made)

. replace id=37 if fip==40
(16,761 real changes made)

. replace id=38 if fip==41
(14,956 real changes made)

. replace id=39 if fip==42
(55,249 real changes made)

. 
. replace id=40 if fip==44
(12,248 real changes made)

. replace id=41 if fip==45
(14,929 real changes made)

. replace id=42 if fip==46
(17,939 real changes made)

. replace id=43 if fip==47
(16,768 real changes made)

. replace id=44 if fip==48
(57,434 real changes made)

. replace id=45 if fip==49
(16,056 real changes made)

. replace id=46 if fip==50
(11,910 real changes made)

. replace id=47 if fip==51
(21,127 real changes made)

. replace id=48 if fip==53
(16,135 real changes made)

. replace id=49 if fip==54
(16,894 real changes made)

. replace id=50 if fip==55
(18,547 real changes made)

. replace id=51 if fip==56
(13,111 real changes made)

. label var id "State ID"

. 
. 
. *age
. rename age age_raw

. gen age = age_raw

. label var age "Age raw"

. recode age 18/24=1 25/34=2 35/44=3 45/54=4 55/64=5 65/99=6, generate (agegroup)
(1250237 differences between age and agegroup)

. label define agegroup 1 "18–24" 2 "25–34" 3 "35–44" 4 "45–54" 5 "55–64" 6 "65+"

. label values agegroup agegroup

. label var agegroup "Age group"

. 
. *sex 
. rename sex sex_raw

. gen female=sex_raw

. recode female(2=1)(1=0)
(1250237 changes made to female)

. label define gender 1 "Female" 0 "Male"

. label var female gender

. label var female "Female"

. 
. *race
. rename race race_raw

. gen race4=race_raw

. label var race4

. recode race4 (100=1)(200=2)(300=5)(650=4)(700=5)
(1250237 changes made to race4)

. label define ra 1 "White" 2 "Black" 4 "Asian" 5 "Other"

. label values race4 ra

. label var race4 "Race 4"

. 
. gen race5=race_raw

. label var race5 "Race 5"

. recode race5 (100=1)(200=2)(300=3)(650=4)(700=5)
(1250237 changes made to race5)

. label define race5 1 "White" 2 "Black/Negro" 3 "American Indian/Aleut/Eskimo" 4 "Asian or Pacific Islander" 5 "Other (single) race, n.e.c." 

. label values race5 race5

. 
. *hisp 
. rename hispan hispan_raw

. gen hisp=hispan_raw

. label val hisp

. recode hisp (901=.)(902=.)
(19033 changes made to hisp)

. recode hisp (100=1)(102=1)(103=1)(104=1)(108=1)(200=1)(300=1)(600=1)(610=1)
(76203 changes made to hisp)

. label define hi 0 "Not Hispanic" 1 "Hispanic" 

. label values hisp hi

. label var hisp "Hispanic origin"

. 
. *empstat
. rename empstat empstat_raw

. gen empstat=empstat_raw

. recode empstat (0=.)(1=1)(10=2)(12=2)(20=3)(21=3)(22=3)(30=4)(31=4)(32=4)(33=4)(34=4)(35=4)(36=4)
(1248481 changes made to empstat)

. label define emp 1 "Armed Forces" 2 "Employed" 3 "Unemployed" 4 "NILF"

. label values empstat emp

. label var empstat "Employment status"

. 
. *educ
. rename educ educ_raw

. gen educ=educ_raw

. label val educ

. recode educ (1=.) (999=.)(2=0)(10=1)(11=1)(12=1)(13=1)(14=1)(20=2)(21=2)(22=2)(30=2)(31=2)(32=2)(40=3)(50=3)(60=3)(70=4)(71=4)(72=4)(73=4)(80=5)(81=5)(90=5)(91=5)(
> 92=5)(100=5)(110=6)(111=6)(120=7)(121=7)(122=7)(123=7)(124=7)(125=7)
(1250237 changes made to educ)

. label define educc 0 "None" 1 "Grade 1-4" 2 "Grade 5-8" 3 "Grade 9-11" 4 "High School" 5 "Some college" 6 "BA Degree" 7 "Post-Grad"

. label values educ educc

. label var educ "Educational attainment"

. 
. *voted
. rename voted voted_raw

. gen voted=voted_raw

. label val voted

. recode voted(1=0)(2=1)(96=.a)(97=.b)(98=.c)(99=.d)
(1250237 changes made to voted)

. label define vote 0 "Did not vote" 1 "Voted" .a "Refused" .b "Don't know" .c "No response" .d "Not in universe"

. label values voted vote

. label var voted "Voted for the most recent November election"

. 
. 
. merge m:1 year id using data_ubiturnout_aggregate.dta, keepusing(treatyear alaska dividend dividend_nominal dividend_real div1000 dividend_nominal_interaction divi
> dend_real_interaction div1000_interaction lnpop gini lnrgdp_pc edr)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                         1,250,237  (_merge==3)
    -----------------------------------------

. 
. drop _merge

. 
. save data_ubiturnout_individual.dta, replace
(file data_ubiturnout_individual.dta not found)
file data_ubiturnout_individual.dta saved

. 
end of do-file

. do "/Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/replication_ubiturnout_aggregate.do"

. 
. *-----------------------------------------------------------------------------
. **                        Does a UBI affect voter turnout                   **
. **                             Replication File                             **
. *-----------------------------------------------------------------------------
. 
. *FIGURES AND TABLES IN THE PAPER
. 
. 
. use "data_ubiturnout_aggregate.dta", clear

. 
. 
. * set panel data
. xtset id t

Panel variable: id (strongly balanced)
 Time variable: t, 1 to 12
         Delta: 1 unit

. 
. 
. *-----------------------------------------------------------------------------
. *                                 MAIN PAPER                                **
. *-----------------------------------------------------------------------------
. 
. ** Figure 1 : Turnout development over time
. 
. sort year id

. egen cpsturnus=mean(turnout) if id!=2, by(year)
(12 missing values generated)

. label var cpsturnus "Turnout U.S. (excl. Alaska)"

. egen cpsturnak=mean(turnout) if id==2, by(year)
(600 missing values generated)

. label var cpsturnak "Turnout Alaska"

. 
. egen epturnus=mean(turnoutep) if id!=2, by(year)
(62 missing values generated)

. label var epturnus "Turnout U.S. (excl. Alaska)"

. egen epturnak=mean(turnoutep) if id==2, by(year)
(601 missing values generated)

. label var epturnak "Turnout Alaska"

. 
. graph drop _all

. 
. twoway (line cpsturnak year) (line cpsturnus year), xline(1982, lpattern(dot)) xlabel(1978[2]2000) scheme(s2mono) xlabel(, angle(45)) ylabel(0.4(0.05)0.7) title("T
> urnout CPS") name(cps)

. 
. twoway (line epturnak year) (line epturnus year), xline(1982, lpattern(dot)) xlabel(1978[2]2000) scheme(s2mono) xlabel(, angle(45)) ylabel(0.4(0.05)0.7) title("Tur
> nout Elections Project") name(ep)

. 
. grc1leg cps ep, rows(1) scheme(s2mono)

. 
. 
. 
. **Table 1 : DiD Fixed-Effects Model, CPS data ***
. 
. eststo CPS1: quietly xtreg turnout treatyear alaska dividend i.year if year<1984, ///
> fe vce(cluster id)

. eststo CPS4: quietly xtreg turnout treatyear alaska dividend i.year if year<1992, ///
> fe vce(cluster id)

. eststo CPS7: quietly xtreg turnout treatyear alaska dividend i.year, ///
> fe vce(cluster id)

. eststo CPS2: quietly xtreg turnout treatyear alaska dividend i.year lnpop ///
> lnrgdp_pc africanamerican if year<1984, fe vce(cluster id)

. eststo CPS5: quietly xtreg turnout treatyear alaska dividend i.year lnpop ///
> lnrgdp_pc africanamerican if year<1992, fe vce(cluster id)

. eststo CPS8: quietly xtreg turnout treatyear alaska dividend i.year lnpop ///
> lnrgdp_pc africanamerican, fe vce(cluster id)

. eststo CPS3: quietly xtreg turnout treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr if year<1984, fe vce(cluster id)

. eststo CPS6: quietly xtreg turnout treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr if year<1992, fe vce(cluster id)

. eststo CPS9: quietly xtreg turnout treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr, fe vce(cluster id)

. 
. esttab CPS1 CPS2 CPS3 CPS4 CPS5 CPS6 CPS7 CPS8 CPS9 using Table1.rtf, indicate ("Year FEs = *year*") replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Wi
> thin R2")) onecell nogaps varwidth(14) modelwidth(6) varlabels(_cons Constant) drop(alaska) label title("DiD Fixed-Effects Model, CPS data") mlabels("Short-Term 19
> 78-1982" "Short-Term 1978-1982" "Short-Term 1978-1982" "Medium-Term 1978-1990" "Medium-Term 1978-1990" "Medium-Term 1978-1990" "Long-Term 1978-2000" "Long-Term 197
> 8-2000" "Long-Term 1978-2000") nonotes addnotes("Notes: Regression coefficients shown with robust standard errors in parentheses. Dividend dummy is coded 1 for Ala
> ska after the introduction of the dividend and 0 otherwise and is an interaction of a dummy for Alaska and a dummy for the treatment period starting in 1982. The e
> stimates for the Alaska and the treatment dummy are not reported. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to Table1.rtf)

. 
. 
. 
. ** Table 2 : Generalized Differences-in-Differences Model Estimates**********
. 
. 
. eststo GDD1: xtreg turnout i.alaska##c.div1000 i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if year<1984, fe vce(cluster id)
note: 1.alaska omitted because of collinearity.
note: 1982.year omitted because of collinearity.
note: edr omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        153
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.8009                                         min =          3
     Between = 0.2204                                         avg =        3.0
     Overall = 0.2264                                         max =          3

                                                F(8,50)           =          .
corr(u_i, Xb) = -0.9335                         Prob > F          =          .

                                        (Std. err. adjusted for 51 clusters in id)
----------------------------------------------------------------------------------
                 |               Robust
         turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        1.alaska |          0  (omitted)
         div1000 |   .0188642   .0096166     1.96   0.055    -.0004513    .0381797
                 |
alaska#c.div1000 |
              1  |    .075885    .010671     7.11   0.000     .0544518    .0973183
                 |
            year |
           1980  |     .14011   .0123964    11.30   0.000      .115211    .1650089
           1982  |          0  (omitted)
                 |
           lnpop |   .0364796   .1650056     0.22   0.826    -.2949439    .3679031
       lnrgdp_pc |  -.3334714   .0818509    -4.07   0.000    -.4978737   -.1690691
 africanamerican |   -1.74112   1.471649    -1.18   0.242    -4.697014    1.214774
    unemployment |  -.5443076   .4035258    -1.35   0.183    -1.354813    .2661977
            gini |   .0599716   .3012964     0.20   0.843       -.5452    .6651432
           pop65 |  -.2479526   2.589116    -0.10   0.924    -5.448346     4.95244
             edr |          0  (omitted)
           _cons |   3.617645    2.74171     1.32   0.193    -1.889241    9.124532
-----------------+----------------------------------------------------------------
         sigma_u |  .22666051
         sigma_e |  .03840849
             rho |  .97208691   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. 
. xtreg turnout div1000_interaction i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if year<1984, fe vce(cluster id)
note: edr omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        153
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.8009                                         min =          3
     Between = 0.2204                                         avg =        3.0
     Overall = 0.2264                                         max =          3

                                                F(8,50)           =          .
corr(u_i, Xb) = -0.9335                         Prob > F          =          .

                                           (Std. err. adjusted for 51 clusters in id)
-------------------------------------------------------------------------------------
                    |               Robust
            turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
div1000_interaction |    .075885    .010671     7.11   0.000     .0544517    .0973182
                    |
               year |
              1980  |     .14011   .0123964    11.30   0.000      .115211    .1650089
              1982  |   .0451973   .0230407     1.96   0.055    -.0010813    .0914758
                    |
              lnpop |   .0364796   .1650056     0.22   0.826    -.2949439    .3679031
          lnrgdp_pc |  -.3334714   .0818509    -4.07   0.000    -.4978737   -.1690691
    africanamerican |   -1.74112   1.471649    -1.18   0.242    -4.697014    1.214774
       unemployment |  -.5443076   .4035258    -1.35   0.183    -1.354813    .2661977
               gini |   .0599716   .3012964     0.20   0.843       -.5452    .6651432
              pop65 |  -.2479526   2.589116    -0.10   0.924    -5.448346     4.95244
                edr |          0  (omitted)
              _cons |   3.617645    2.74171     1.32   0.193    -1.889241    9.124532
--------------------+----------------------------------------------------------------
            sigma_u |  .22666051
            sigma_e |  .03840849
                rho |  .97208691   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. 
. eststo GDD2: xtreg turnout i.alaska##c.div1000 i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if year<1992, fe vce(cluster id)
note: 1.alaska omitted because of collinearity.
note: 1990.year omitted because of collinearity.
note: edr omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        357
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.7203                                         min =          7
     Between = 0.1786                                         avg =        7.0
     Overall = 0.2110                                         max =          7

                                                F(12,50)          =          .
corr(u_i, Xb) = -0.9008                         Prob > F          =          .

                                        (Std. err. adjusted for 51 clusters in id)
----------------------------------------------------------------------------------
                 |               Robust
         turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        1.alaska |          0  (omitted)
         div1000 |   .0034663   .0186767     0.19   0.854     -.034047    .0409795
                 |
alaska#c.div1000 |
              1  |   .0477867   .0055399     8.63   0.000     .0366596    .0589139
                 |
            year |
           1980  |   .1315545   .0096241    13.67   0.000      .112224     .150885
           1982  |   .0009418   .0357858     0.03   0.979    -.0709361    .0728197
           1984  |   .1279088   .0084432    15.15   0.000       .11095    .1448675
           1986  |   .0007495   .0075337     0.10   0.921    -.0143825    .0158815
           1988  |   .1177064    .009207    12.78   0.000     .0992136    .1361992
           1990  |          0  (omitted)
                 |
           lnpop |   .0493951   .0595179     0.83   0.411    -.0701501    .1689403
       lnrgdp_pc |    -.01628   .0430495    -0.38   0.707    -.1027474    .0701874
 africanamerican |   -1.59056    .739245    -2.15   0.036    -3.075377   -.1057427
    unemployment |   .6539021   .2313236     2.83   0.007     .1892749    1.118529
            gini |   -.036936   .1298747    -0.28   0.777     -.297797     .223925
           pop65 |   .3474625   1.077989     0.32   0.749    -1.817743    2.512668
             edr |          0  (omitted)
           _cons |   .0187931   1.094644     0.02   0.986    -2.179864     2.21745
-----------------+----------------------------------------------------------------
         sigma_u |  .17664095
         sigma_e |  .04261115
             rho |  .94500803   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. eststo GDD3: xtreg turnout i.alaska##c.div1000 i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr, fe vce(cluster id)
note: 1.alaska omitted because of collinearity.
note: 2000.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        612
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.7337                                         min =         12
     Between = 0.2882                                         avg =       12.0
     Overall = 0.4115                                         max =         12

                                                F(18,50)          =          .
corr(u_i, Xb) = -0.7002                         Prob > F          =          .

                                        (Std. err. adjusted for 51 clusters in id)
----------------------------------------------------------------------------------
                 |               Robust
         turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        1.alaska |          0  (omitted)
         div1000 |   .0387728   .0092293     4.20   0.000     .0202351    .0573104
                 |
alaska#c.div1000 |
              1  |   .0426976   .0054937     7.77   0.000     .0316631     .053732
                 |
            year |
           1980  |   .1339342   .0084047    15.94   0.000      .117053    .1508155
           1982  |  -.0749072    .021834    -3.43   0.001    -.1187621   -.0310522
           1984  |   .1057412   .0083879    12.61   0.000     .0888937    .1225887
           1986  |  -.0395015   .0118032    -3.35   0.002    -.0632088   -.0157941
           1988  |   .0509674   .0081195     6.28   0.000     .0346589    .0672758
           1990  |  -.0720618   .0124507    -5.79   0.000    -.0970697   -.0470539
           1992  |    .099504   .0111946     8.89   0.000     .0770189    .1219891
           1994  |  -.0624084   .0115401    -5.41   0.000    -.0855873   -.0392294
           1996  |   .0235093   .0089112     2.64   0.011     .0056107    .0414079
           1998  |  -.1171821   .0097646   -12.00   0.000     -.136795   -.0975693
           2000  |          0  (omitted)
                 |
           lnpop |  -.0429635   .0347488    -1.24   0.222    -.1127586    .0268316
       lnrgdp_pc |  -.0068318   .0291051    -0.23   0.815    -.0652912    .0516276
 africanamerican |  -.7106655   .6233762    -1.14   0.260    -1.962753    .5414223
    unemployment |   .3940868   .1765962     2.23   0.030     .0393829    .7487906
            gini |   .2023867   .1174087     1.72   0.091    -.0334356     .438209
           pop65 |  -.0000918   .7857808    -0.00   1.000    -1.578379    1.578196
             edr |  -.0047458   .0226805    -0.21   0.835    -.0503009    .0408094
           _cons |   1.135348   .6237808     1.82   0.075     -.117553    2.388248
-----------------+----------------------------------------------------------------
         sigma_u |  .08834449
         sigma_e |  .04286951
             rho |  .80940769   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. **post 1982
. eststo GDD4: xtreg turnout i.alaska##c.div1000 i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if year>1980 & year<1992, fe vce(cluster id)
note: 1.alaska omitted because of collinearity.
note: 1990.year omitted because of collinearity.
note: edr omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        255
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.7055                                         min =          5
     Between = 0.0799                                         avg =        5.0
     Overall = 0.1290                                         max =          5

                                                F(10,50)          =          .
corr(u_i, Xb) = -0.9092                         Prob > F          =          .

                                        (Std. err. adjusted for 51 clusters in id)
----------------------------------------------------------------------------------
                 |               Robust
         turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        1.alaska |          0  (omitted)
         div1000 |   .0113104   .0416056     0.27   0.787    -.0722568    .0948776
                 |
alaska#c.div1000 |
              1  |   .0683245   .0168324     4.06   0.000     .0345155    .1021334
                 |
            year |
           1984  |   .1426928    .060243     2.37   0.022     .0216912    .2636944
           1986  |   .0092684   .0351017     0.26   0.793    -.0612355    .0797723
           1988  |   .1215075   .0129551     9.38   0.000     .0954864    .1475285
           1990  |          0  (omitted)
                 |
           lnpop |   .0931961   .1146019     0.81   0.420    -.1369886    .3233807
       lnrgdp_pc |   .0132773   .0689023     0.19   0.848    -.1251169    .1516716
 africanamerican |  -1.570154   1.337148    -1.17   0.246    -4.255895    1.115587
    unemployment |   .9874409   .3085573     3.20   0.002     .3676854    1.607196
            gini |   .0388393   .2052099     0.19   0.851    -.3733368    .4510155
           pop65 |   .7193775   1.038009     0.69   0.491    -1.365524    2.804279
             edr |          0  (omitted)
           _cons |  -1.070257   1.855405    -0.58   0.567    -4.796947    2.656433
-----------------+----------------------------------------------------------------
         sigma_u |  .18965458
         sigma_e |  .04324358
             rho |  .95057972   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. eststo GDD5: xtreg turnout i.alaska##c.div1000 i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if year>1980, fe vce(cluster id)
note: 1.alaska omitted because of collinearity.
note: 2000.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        510
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.7352                                         min =         10
     Between = 0.2875                                         avg =       10.0
     Overall = 0.4496                                         max =         10

                                                F(16,50)          =          .
corr(u_i, Xb) = -0.6108                         Prob > F          =          .

                                        (Std. err. adjusted for 51 clusters in id)
----------------------------------------------------------------------------------
                 |               Robust
         turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
        1.alaska |          0  (omitted)
         div1000 |   .2438011   .0847689     2.88   0.006     .0735377    .4140645
                 |
alaska#c.div1000 |
              1  |   .0505499   .0085241     5.93   0.000     .0334288    .0676711
                 |
            year |
           1984  |   .5225947   .1516145     3.45   0.001     .2180681    .8271214
           1986  |   .2879411    .115646     2.49   0.016     .0556592    .5202229
           1988  |   .2844677   .0840668     3.38   0.001     .1156147    .4533208
           1990  |    .143823   .0776641     1.85   0.070    -.0121699    .2998159
           1992  |   .3484279   .0927425     3.76   0.000     .1621492    .5347067
           1994  |   .1779292   .0876509     2.03   0.048     .0018773    .3539811
           1996  |   .2325516   .0812669     2.86   0.006     .0693223    .3957809
           1998  |  -.0200973   .0355006    -0.57   0.574    -.0914023    .0512076
           2000  |          0  (omitted)
                 |
           lnpop |  -.0717848   .0480196    -1.49   0.141     -.168235    .0246654
       lnrgdp_pc |   -.005237   .0342965    -0.15   0.879    -.0741235    .0636496
 africanamerican |  -.2260196   .7299269    -0.31   0.758    -1.692121    1.240082
    unemployment |   .3921017   .2048768     1.91   0.061    -.0194054    .8036088
            gini |   .2560446   .1373882     1.86   0.068    -.0199077    .5319968
           pop65 |  -.1808046   1.000788    -0.18   0.857    -2.190946    1.829336
             edr |   .0091685   .0242889     0.38   0.707    -.0396173    .0579542
           _cons |   .9224608   .7421616     1.24   0.220    -.5682146    2.413136
-----------------+----------------------------------------------------------------
         sigma_u |  .07503096
         sigma_e |   .0426932
             rho |  .75541831   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. 
. esttab GDD1 GDD2 GDD3 GDD4 GDD5 using Table2.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth(14) modelwidth(6
> ) varlabels(_cons Constant) drop(lnrgdp_pc africanamerican unemployment gini pop65 edr) label title("Generalized DiD Model Estimates") mlabels("Short-Term 1978-198
> 2" "Medium-Term 1978-1990" "Long-Term 1978-2000" "Post-Introduction 1982-1990" "Post-Introduction 1982-2000") nonotes addnotes("Notes: Regression coefficients show
> n with robust standard errors in parentheses. Dividend in USD / 1000 is the dividend payment in 2016 dollars and is an interaction of a dummy for Alaska and the di
> vidend payments starting in 1982. The estimates for the Alaska and the payment amount dummy are not reported. Coefficients for the fixed effects are not reported. 
> The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to Table2.rtf)

. 
. 
. 
. ** Table 4 : Parallel Trends Assumption****************
. 
. * Model (1) Placebo Dividend 
. 
. gen treatnew = 0

. replace treatnew = 1 if year==1980
(51 real changes made)

. 
. gen placebodiv = treatnew*alaska

. label variable placebodiv "Placebo dividend"

. 
. eststo P1 : xtreg turnout treatnew alaska placebodiv i.year if year<1982, fe 
note: alaska omitted because of collinearity.
note: 1980.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        102
Group variable: id                              Number of groups  =         51

R-squared:                                      Obs per group:
     Within  = 0.8579                                         min =          2
     Between = 0.0001                                         avg =        2.0
     Overall = 0.4544                                         max =          2

                                                F(2,49)           =     147.88
corr(u_i, Xb) = -0.0056                         Prob > F          =     0.0000

------------------------------------------------------------------------------
     turnout | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    treatnew |     .14006   .0081586    17.17   0.000     .1236647    .1564553
      alaska |          0  (omitted)
  placebodiv |    -.08106   .0582641    -1.39   0.170     -.198146     .036026
             |
        year |
       1980  |          0  (omitted)
             |
       _cons |   .4742157   .0057122    83.02   0.000     .4627367    .4856947
-------------+----------------------------------------------------------------
     sigma_u |  .07117075
     sigma_e |  .04079301
         rho |  .75271448   (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(50, 49) = 6.07                      Prob > F = 0.0000

. 
. * Models (2-4) Synthetic control method, following Abadie et al. (2010; 2015)
. tsset id year

Panel variable: id (strongly balanced)
 Time variable: year, 1978 to 2000, but with gaps
         Delta: 1 unit

. sort year id

. synth turnout lnpop lnrgdp_pc africanamerican unemp gini pop65 edr ///    
> turnout(1978) turnout(1980), trunit(2) trperiod(1982) xperiod(1978 1980) nested
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Synthetic Control Method for Comparative Case Studies
---------------------------------------------------------------------------------------------------------------------------------------------------------------------

First Step: Data Setup
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Data Setup successful
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
                Treated Unit: 2
               Control Units: 1 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
                              50 51
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
          Dependent Variable: turnout
  MSPE minimized for periods: 1978 1980
Results obtained for periods: 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
                  Predictors: lnpop lnrgdp_pc africanamerican unemp gini pop65 edr turnout(1978) turnout(1980)
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unless period is specified
predictors are averaged over: 1978 1980
---------------------------------------------------------------------------------------------------------------------------------------------------------------------

Second Step: Run Optimization
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Nested optimization requested
Starting nested optimization module
Optimization done
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Optimization done
---------------------------------------------------------------------------------------------------------------------------------------------------------------------

Third Step: Obtain Results
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Loss: Root Mean Squared Prediction Error

---------------------
   RMSPE |  1.94e-13 
---------------------
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unit Weights:

-----------------------
    Co_No | Unit_Weight
----------+------------
        1 |        .011
        3 |        .006
        4 |        .006
        5 |        .026
        6 |        .005
        7 |        .004
        8 |        .008
        9 |           0
       10 |        .012
       11 |        .004
       12 |        .028
       13 |        .003
       14 |        .004
       15 |        .004
       16 |        .003
       17 |        .006
       18 |        .003
       19 |        .003
       20 |        .005
       21 |        .007
       22 |        .006
       23 |        .006
       24 |        .003
       25 |        .004
       26 |        .004
       27 |        .006
       28 |        .006
       29 |        .258
       30 |        .004
       31 |        .005
       32 |        .011
       33 |        .014
       34 |        .004
       35 |        .003
       36 |        .005
       37 |         .01
       38 |        .005
       39 |         .02
       40 |        .007
       41 |        .006
       42 |        .003
       43 |        .008
       44 |        .006
       45 |        .003
       46 |        .003
       47 |        .009
       48 |        .004
       49 |        .005
       50 |        .003
       51 |        .419
-----------------------
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
Predictor Balance:

------------------------------------------------------
                               |   Treated  Synthetic 
-------------------------------+----------------------
                         lnpop |  12.90759   13.80964 
                     lnrgdp_pc |  11.40577   10.65944 
               africanamerican |  .0336392   .0500922 
                         unemp |  .1012577    .048596 
                          gini |  .5015501   .4885689 
                         pop65 |  .0273931   .0901289 
                           edr |         0       .011 
                 turnout(1978) |      .509    .508084 
                 turnout(1980) |      .568    .566866 
------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. ereturn list

matrices:
              e(RMSPE) :  1 x 1
           e(V_matrix) :  9 x 9
          e(X_balance) :  9 x 2
          e(W_weights) :  50 x 2
        e(Y_synthetic) :  12 x 1
          e(Y_treated) :  12 x 1

. 
. g w=1

. replace w=0.011 if id==1
(12 real changes made)

. replace w=0.006 if id==3
(12 real changes made)

. replace w=0.006 if id==4
(12 real changes made)

. replace w=.026 if id==5
(12 real changes made)

. replace w=.005 if id==6
(12 real changes made)

. replace w=.004 if id==7
(12 real changes made)

. replace w=.008 if id==8
(12 real changes made)

. replace w=0 if id==9
(12 real changes made)

. replace w=.012 if id==10
(12 real changes made)

. replace w=.004 if id==11
(12 real changes made)

. replace w=.028 if id==12
(12 real changes made)

. replace w=.003 if id==13
(12 real changes made)

. replace w=.004 if id==14
(12 real changes made)

. replace w=.004 if id==15
(12 real changes made)

. replace w=.003 if id==16
(12 real changes made)

. replace w=.006 if id==17
(12 real changes made)

. replace w=.003 if id==18
(12 real changes made)

. replace w=.003 if id==19
(12 real changes made)

. replace w=.005 if id==20
(12 real changes made)

. replace w=.007 if id==21
(12 real changes made)

. replace w=.006 if id==22
(12 real changes made)

. replace w=.006 if id==23
(12 real changes made)

. replace w=.003 if id==24
(12 real changes made)

. replace w=.004 if id==25
(12 real changes made)

. replace w=.004 if id==26
(12 real changes made)

. replace w=.006 if id==27
(12 real changes made)

. replace w=.006 if id==28
(12 real changes made)

. replace w=.258 if id==29
(12 real changes made)

. replace w=.004 if id==30
(12 real changes made)

. replace w=.005 if id==31
(12 real changes made)

. replace w=.011 if id==32
(12 real changes made)

. replace w=.014 if id==33
(12 real changes made)

. replace w=.004 if id==34
(12 real changes made)

. replace w=.003 if id==35
(12 real changes made)

. replace w=.005 if id==36
(12 real changes made)

. replace w=.01 if id==37
(12 real changes made)

. replace w=.005 if id==38
(12 real changes made)

. replace w=.02 if id==39
(12 real changes made)

. replace w=.007 if id==40
(12 real changes made)

. replace w=.006 if id==41
(12 real changes made)

. replace w=.003 if id==42
(12 real changes made)

. replace w=.008 if id==43
(12 real changes made)

. replace w=.006 if id==44
(12 real changes made)

. replace w=.003 if id==45
(12 real changes made)

. replace w=.003 if id==46
(12 real changes made)

. replace w=.009 if id==47
(12 real changes made)

. replace w=.004 if id==48
(12 real changes made)

. replace w=.005 if id==49
(12 real changes made)

. replace w=.003 if id==50
(12 real changes made)

. replace w=.419 if id==51
(12 real changes made)

. 
. xtset id t 

Panel variable: id (strongly balanced)
 Time variable: t, 1 to 12
         Delta: 1 unit

. eststo PS1: xtreg turnout treatyear alaska dividend i.year [aw=w] if year<1984, fe vce(cluster id)
note: alaska omitted because of collinearity.
note: 1982.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        150
Group variable: id                              Number of groups  =         50

R-squared:                                      Obs per group:
     Within  = 0.6742                                         min =          3
     Between = 0.0016                                         avg =        3.0
     Overall = 0.3697                                         max =          3

                                                F(2,49)           =          .
corr(u_i, Xb) = -0.0002                         Prob > F          =          .

                                    (Std. err. adjusted for 50 clusters in id)
------------------------------------------------------------------------------
             |               Robust
     turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   treatyear |   .0125772   .0042479     2.96   0.005     .0040407    .0211136
      alaska |          0  (omitted)
    dividend |   .0633978    .010438     6.07   0.000     .0424219    .0843737
             |
        year |
       1980  |   .0589499   .0138156     4.27   0.000     .0311864    .0867135
       1982  |          0  (omitted)
             |
       _cons |   .5090511    .005259    96.80   0.000     .4984827    .5196195
-------------+----------------------------------------------------------------
     sigma_u |  .07041411
     sigma_e |  .02522293
         rho |  .88627862   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. eststo PS2: xtreg turnout treatyear alaska dividend i.year [aw=w] if year<1992, fe vce(cluster id)
note: alaska omitted because of collinearity.
note: 1990.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        350
Group variable: id                              Number of groups  =         50

R-squared:                                      Obs per group:
     Within  = 0.5777                                         min =          7
     Between = 0.0052                                         avg =        7.0
     Overall = 0.3815                                         max =          7

                                                F(6,49)           =          .
corr(u_i, Xb) = -0.0033                         Prob > F          =          .

                                    (Std. err. adjusted for 50 clusters in id)
------------------------------------------------------------------------------
             |               Robust
     turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   treatyear |   .0015977   .0190437     0.08   0.933     -.036672    .0398673
      alaska |          0  (omitted)
    dividend |   .0547429   .0020028    27.33   0.000     .0507181    .0587676
             |
        year |
       1980  |   .0589499   .0138151     4.27   0.000     .0311875    .0867124
       1982  |   .0153113   .0160027     0.96   0.343    -.0168473    .0474699
       1984  |   .0526256   .0319815     1.65   0.106    -.0116435    .1168948
       1986  |  -.0126847   .0095044    -1.33   0.188    -.0317846    .0064152
       1988  |   .0419199   .0222353     1.89   0.065    -.0027636    .0866034
       1990  |          0  (omitted)
             |
       _cons |   .5090511   .0064432    79.01   0.000      .496103    .5219991
-------------+----------------------------------------------------------------
     sigma_u |  .06237209
     sigma_e |  .02815712
         rho |  .83070545   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. eststo PS3: xtreg turnout treatyear alaska dividend i.year [aw=w], fe vce(cluster id)
note: alaska omitted because of collinearity.
note: 2000.year omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =        600
Group variable: id                              Number of groups  =         50

R-squared:                                      Obs per group:
     Within  = 0.7074                                         min =         12
     Between = 0.0144                                         avg =       12.0
     Overall = 0.3974                                         max =         12

                                                F(11,49)          =          .
corr(u_i, Xb) = -0.0008                         Prob > F          =          .

                                    (Std. err. adjusted for 50 clusters in id)
------------------------------------------------------------------------------
             |               Robust
     turnout | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   treatyear |   .0669196   .0115241     5.81   0.000     .0437611    .0900781
      alaska |          0  (omitted)
    dividend |   .0614087   .0050645    12.13   0.000     .0512313    .0715862
             |
        year |
       1980  |   .0589499   .0138149     4.27   0.000     .0311878    .0867121
       1982  |  -.0533468   .0109788    -4.86   0.000    -.0754096   -.0312841
       1984  |  -.0160325   .0273193    -0.59   0.560    -.0709327    .0388676
       1986  |  -.0813428   .0089878    -9.05   0.000    -.0994046   -.0632811
       1988  |  -.0267382   .0186472    -1.43   0.158    -.0642112    .0107347
       1990  |  -.0686582   .0073228    -9.38   0.000    -.0833739   -.0539424
       1992  |   .0461582   .0136685     3.38   0.001     .0186903     .073626
       1994  |  -.0494234   .0143227    -3.45   0.001    -.0782059   -.0206409
       1996  |  -.0209189   .0239432    -0.87   0.387    -.0690346    .0271968
       1998  |  -.1112302   .0082014   -13.56   0.000    -.1277116   -.0947488
       2000  |          0  (omitted)
             |
       _cons |   .5090511   .0049832   102.15   0.000      .499037    .5190651
-------------+----------------------------------------------------------------
     sigma_u |  .05788837
     sigma_e |   .0295936
         rho |  .79280502   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. 
. esttab P1 PS1 PS2 PS3 using Table4.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth(14) modelwidth(6) varlabel
> s(_cons Constant) drop(treatyear alaska treatnew) label title("Parallel Trends Assumption") mlabels("1978-1980" "1978-1982" "1978-1990" "1978-2000") nonotes addnot
> es("Notes: Regression coefficients shown with robust standard errors in parentheses. The dividend in Model 1 is a Placebo dividend that coded 1 for Alaska in 1980,
>  after the placebo introduction of the treatment and 0 otherwise. Standard errors in Models 2-4 are clustered by the state. The synthetic control group was constru
> cted using the covariates population size, GDP per capita, %Africanamerican, Unemployment rate, the Gini coefficient, % Population aged 65+ and EDR. The significan
> ce of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to Table4.rtf)

. 
. 
. ** Table 6 : Comparing Midterm and Presidential Elections
. 
. eststo CPSMP1: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr i.year if year<1986 & president==0, fe vce(cluster id)

. eststo CPSMP4: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr i.year if year<1986 & president==1, fe vce(cluster id)

. 
. eststo CPSMP2: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemployment gini pop65 edr i.year if year<1992 & president==0, fe vce(cluster id)

. eststo CPSMP5: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr i.year if year<1992 & president==1, fe vce(cluster id)

. 
. eststo CPSMP3: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr i.year if president==0, fe vce(cluster id)

. eststo CPSMP6: quietly xtreg turnout treatyear alaska dividend lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr i.year if president==1, fe vce(cluster id)

. 
. esttab CPSMP1 CPSMP2 CPSMP3 CPSMP4 CPSMP5 CPSMP6 using Table6.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth
> (14) modelwidth(6) varlabels(_cons Constant) drop(treatyear alaska) label title("Comparing Midterm and Presidential Elections") mlabels("Midterm: 1978-1982" "Midte
> rm: 1978-1990" "Midterm: 1978-2000" "Presidential: 1978-1984" "Presidential: 1978-1990" "Presidential: 1978-2000") nonotes addnotes("Notes: Regression coefficients
>  shown with robust standard errors in parentheses. Dividend dummy is coded 1 for Alaska after the introduction of the dividend and 0 otherwise. The significance of
>  the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to Table6.rtf)

. 
. 
. 
. *-----------------------------------------------------------------------------
. ***                               APPENDIX                                 ***
. *-----------------------------------------------------------------------------
. 
. 
. ** Table A3 : Variable Summary Statistics***********************
. 
. gen cpspresi=turnout if president == 1
(306 missing values generated)

. gen cpsmid=turnout if president == 0
(306 missing values generated)

. 
. *Alaska 
. tabstat turnout cpspres cpsmid dividend_real pop rgdp_pc africanamerican unemp gini pop65 edr if id==2, statistics(mean median sd min max n)

   Stats |   turnout  cpspresi    cpsmid  divi~eal       pop   rgdp_pc  africa~n  unempl~t      gini     pop65       edr
---------+--------------------------------------------------------------------------------------------------------------
    Mean |  .5890833  .6148333  .5633333  1456.408  538175.3   79378.6  .0393066  .0864658  .5940789  .0392919         0
     p50 |     .5915     .5945     .5735  1598.875    548780  75309.14  .0402298  .0885382  .5819089   .038445         0
      SD |  .0467595  .0453141  .0341389  865.7088  80664.46  20896.96  .0033724  .0159628   .080515    .01044         0
     Min |      .509      .568      .509         0    402051  57530.85  .0327819   .063466  .4943701  .0258276         0
     Max |      .686      .686      .594   2744.28    627963    125020  .0433096  .1093673  .6951078   .057497         0
       N |        12         6         6        12        12        12        12        12        12        12        12
------------------------------------------------------------------------------------------------------------------------

. 
. *All other U.S. States
. tabstat turnout cpspresi cpsmid pop rgdp_pc africanamerican unemp gini pop65 edr if id!=2, statistics(mean median sd min max n)

   Stats |   turnout  cpspresi    cpsmid       pop   rgdp_pc  africa~n  unempl~t      gini     pop65       edr
---------+----------------------------------------------------------------------------------------------------
    Mean |   .539155  .6021167  .4761933   4986105  39662.12  .1093973   .060123  .5381432  .1217209       .08
     p50 |     .5415      .601      .471   3358901  37406.88  .0720667  .0569799  .5442824   .122786         0
      SD |  .0975093  .0674753  .0808713   5376669  13472.22  .1220421  .0210996  .0445734  .0187032  .2715196
     Min |      .257      .397      .257    430953  23064.97  .0022255  .0230034  .4389738  .0748895         0
     Max |      .756      .756      .727  3.40e+07  149243.7  .7052974  .1538448  .6556932  .1840536         1
       N |       600       300       300       600       600       600       600       600       600       600
--------------------------------------------------------------------------------------------------------------

. 
. 
. 
. ** Table A4 : The Dividend as a share of PI and Poverty Thresholds*********
. 
. gen divpi = dividend_nominal/pi_pc

. tabstat dividend_nominal pi_pc divpi if id==2, by (year)

Summary statistics: Mean
Group variable: year (year)

    year |  divi~nal     pi_pc     divpi
---------+------------------------------
    1978 |         0  13022.97         0
    1980 |         0  15530.79         0
    1982 |      1000  19424.48  .0514814
    1984 |    331.29   19701.5  .0168155
    1986 |    556.26  20331.09  .0273601
    1988 |    826.93  20419.96  .0404962
    1990 |    952.63   23212.6  .0410393
    1992 |    915.84  24239.56  .0377829
    1994 |     983.9   25713.4  .0382641
    1996 |   1130.68  26953.39  .0419495
    1998 |   1540.88  29220.14  .0527335
    2000 |   1963.86  31974.34  .0614199
---------+------------------------------
   Total |  850.1892  22478.68  .0341119
----------------------------------------

. 
. gen divpoverty = dividend_nominal/poverty

. gen divpoverty_fam4 = (dividend_nominal*4)/poverty_fam4

. 
. tabstat poverty poverty_fam4 divpoverty divpoverty_fam4 ///
> if id==2, by (year)

Summary statistics: Mean
Group variable: year (year)

    year |   poverty  povert~4  divpov~y  divpov~4
---------+----------------------------------------
    1978 |      3311      6662         0         0
    1980 |      4190      8414         0         0
    1982 |      4901      9862    .20404  .4055972
    1984 |      5278     10609  .0627681   .124909
    1986 |      5572     11203  .0998313  .1986111
    1988 |      6022     12092  .1373182  .2735461
    1990 |      6652     13359  .1432096  .2852399
    1992 |      7143     14335   .128215  .2555535
    1994 |      7547     15141  .1303697    .25993
    1996 |      7995     16036  .1414234  .2820354
    1998 |      8316     16660   .185291  .3699592
    2000 |      8791     17604  .2233944  .4462304
---------+----------------------------------------
   Total |  6309.833  12664.75  .1213217   .241801
--------------------------------------------------

. 
. 
. ** Figure A2 : Population Growth Rates
. sort year id

. 
. egen popgrowus=mean(popgrowth) if id!=2, by(year)
(12 missing values generated)

. label var popgrowus "U.S. (excl. Alaska)"

. egen popgrowak=mean(popgrowth) if id==2, by(year)
(600 missing values generated)

. label var popgrowak "Alaska"

. egen popgrowtx=mean(popgrowth) if id==44, by(year)
(600 missing values generated)

. label var popgrowtx "Texas"

. egen popgrowok=mean(popgrowth) if id==37, by(year)
(600 missing values generated)

. label var popgrowok "Oklahoma"

. egen popgrownv=mean(popgrowth) if id==29, by(year)
(600 missing values generated)

. label var popgrownv "Nevada"

. 
. line popgrowus popgrowak popgrowtx popgrownv popgrowok year if year>1976, lpattern(solid longdash longdash_dot_dot shortdash dot) xline(1982, lpattern(dot)) xlabel
> (1978[2]2000) scheme(s2mono) xlabel(, angle(45)) 

. 
. 
. 
. ** Table A5 : Robustness - DiD Estimations with Elections Project Data *************
. 
. eststo EP1: quietly xtreg turnoutep treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr if year<1984, fe vce(cluster id)

. eststo EP2: quietly xtreg turnoutep treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr if year<1992, fe vce(cluster id)

. eststo EP3: quietly xtreg turnoutep treatyear alaska dividend i.year lnpop lnrgdp_pc ///
> africanamerican unemp gini pop65 edr, fe vce(cluster id)

. 
. 
. * Table Output to Word
. esttab EP1 EP2 EP3 using TableA5.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth(14) modelwidth(6) varlabels(
> _cons Constant) drop(alaska treatyear) label title("DiD Estimations with Elections Project Data") mlabels("Short-Term 1980-1982" "Medium-Term 1980-1990" "Long-Term
>  1980-2000") nonotes addnotes("Notes: Regression coefficients shown with robust standard errors in parentheses. Number of Observations is denoted as N. of Obs. Div
> idend dummy is coded 1 for Alaska after the introduction of dividend and 0 otherwise. Coefficients for the fixed effects are not reported. The significance of the 
> estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA5.rtf)

. 
. 
. 
. ** Table A6 : Robustness - DiD Estimations Comparing Only Singe Years, CPS Data*****
. 
. gen dp90 = 0

. replace dp90 = 1 if year==1978 | year==1980 | year==1990
(153 real changes made)

. 
. gen dp00 = 0

. replace dp00 = 1 if year==1978 | year==1980 | year==2000
(153 real changes made)

. 
. eststo DP1P: quietly xtreg turnout treatyear alaska dividend i.year if dp90, fe vce(cluster id)

. eststo DP3P: quietly xtreg turnout treatyear alaska dividend i.year if dp00, fe vce(cluster id)

. eststo DP2P: quietly xtreg turnout treatyear alaska dividend i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if dp90, fe vce(cluster id)

. eststo DP4P: quietly xtreg turnout treatyear alaska dividend i.year lnpop lnrgdp_pc africanamerican unemp gini pop65 edr if dp00, fe vce(cluster id)

. 
. * Table Output to Word
. esttab DP1P DP2P DP3P DP4P using TableA6.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels ("N. of Obs." "Within R2")) onecell nogaps varwidth(14) modelwidth(6) v
> arlabels(_cons Constant) drop(alaska treatyear) label title("DiD Estimations Comparing Only Singe Years, CPS Data")  mlabels("Medium Term Pre-Introduction period &
>  1990" "Medium Term Pre-Introduction period & 1990" "Long-Term Pre-introduction period & 2000" "Long-Term Pre-introduction period & 2000")nonotes addnotes("Notes: 
> Regression coefficients shown with robust standard errors in parentheses. Number of Observations is denoted as N. of Obs. Dividend dummy is coded 1 for Alaska afte
> r the introduction of the dividend and 0 otherwise. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA6.rtf)

. 
. 
. 
. 
. 
. 
. 
. 
. 
end of do-file

. do "/Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/replication_ubiturnout_individual.do"

. 
. *-----------------------------------------------------------------------------
. **                        Does a UBI affect voter turnout                   **
. **                       Individual Data Replication File                   **
. *-----------------------------------------------------------------------------
. 
. 
. use "data_ubiturnout_individual.dta", clear

. 
. ** Table 3 : Linear Probability Model, Individual Level DiD Estimates, CPS Voter Supplement
. 
. eststo I1: quietly reg voted i.treatyear##i.alaska i.year i.id if year<1984, vce(cluster id)

. eststo I4: quietly reg voted i.treatyear##i.alaska i.year i.id if year<1992, vce(cluster id)

. eststo I7: quietly reg voted i.treatyear##i.alaska i.year i.id, vce(cluster id)

. 
. eststo I2: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ i.year i.id if year<1984, vce(cluster id)

. eststo I5: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ i.year i.id if year<1992, vce(cluster id)

. eststo I8: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ i.year i.id, vce(cluster id)

. 
. eststo I3: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr i.year i.id if year<1984, vce(cluster id)

. eststo I6: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr i.year i.id if year<1992, vce(cluster id)

. eststo I9: quietly reg voted i.treatyear##i.alaska agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr i.year i.id, vce(cluster id)

. 
. esttab I1 I2 I3 I4 I5 I6 I7 I8 I9 using Table3.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "R2")) onecell nogaps varwidth(14) modelwidth(6) var
> labels(_cons Constant) label title("Linear Probability Model, Individual Level DiD Estimates") mlabels("1978-1982" "1978-1982" "1978-1982" "1978-1990" "1978-1990" 
> "1978-1990" "1978-2000" "1978-2000" "1978-2000") nonotes addnotes("Notes: Regression coefficients shown with robust standard errors in parentheses that are cluster
> ed by state. Not in labor force is denoted as NILF. Dividend dummy is coded 1 for Alaska after the introduction of the dividend and 0 otherwise and is an interacti
> on of a dummy for Alaska and a dummy for the treatment period starting in 1982. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05,
>  *p<0.1.")
(output written to Table3.rtf)

. 
. 
. 
. ** Table 7 : Heterogenous Effects - Educational Attainment
. 
. graph drop _all

. 
. ***ST
. eststo edst: reg voted alaska treatyear i.dividend##c.educ agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id if year<1984, vce(clust
> er id)
note: educ omitted because of collinearity.
note: 1982.year omitted because of collinearity.
note: 2.id omitted because of collinearity.
note: 50.id omitted because of collinearity.

Linear regression                               Number of obs     =    306,018
                                                F(12, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1624
                                                Root MSE          =     .45152

                                       (Std. err. adjusted for 51 clusters in id)
---------------------------------------------------------------------------------
                |               Robust
          voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
         alaska |   .4805995   .3370609     1.43   0.160    -.1964072    1.157606
      treatyear |   .0152623    .009448     1.62   0.113    -.0037145    .0342391
     1.dividend |   .2771449   .0305901     9.06   0.000     .2157028     .338587
           educ |   .0968543   .0020006    48.41   0.000     .0928359    .1008727
                |
dividend#c.educ |
             1  |  -.0280496   .0030292    -9.26   0.000    -.0341339   -.0219652
                |
       agegroup |   .0914776   .0010906    83.88   0.000      .089287    .0936681
           educ |          0  (omitted)
         female |   .0121178   .0030669     3.95   0.000     .0059577    .0182779
                |
          race4 |
         Black  |   .0168266   .0110848     1.52   0.135     -.005438    .0390911
         Other  |  -.0896627   .0246228    -3.64   0.001     -.139119   -.0402064
                |
           hisp |  -.0194702   .0190062    -1.02   0.311    -.0576453    .0187048
                |
        empstat |
    Unemployed  |  -.0919804   .0048977   -18.78   0.000    -.1018178    -.082143
          NILF  |  -.0640262    .003326   -19.25   0.000    -.0707067   -.0573456
                |
          lnpop |    .092347   .1441231     0.64   0.525    -.1971327    .3818268
      lnrgdp_pc |  -.1729054   .0720426    -2.40   0.020    -.3176072   -.0282036
           gini |   .1277453   .2704566     0.47   0.639    -.4154827    .6709734
            edr |   .0973878   .0313305     3.11   0.003     .0344586    .1603169
                |
           year |
          1980  |   .1319677   .0098396    13.41   0.000     .1122043    .1517311
          1982  |          0  (omitted)
                |
             id |
             2  |          0  (omitted)
             3  |  -.0257921   .0526252    -0.49   0.626     -.131493    .0799088
             4  |   .0440706   .0778218     0.57   0.574    -.1122391    .2003804
             5  |   -.083312   .2628782    -0.32   0.753    -.6113184    .4446943
             6  |   .0816879   .0484198     1.69   0.098    -.0155662     .178942
             7  |   .1200655   .0406576     2.95   0.005     .0384022    .2017287
             8  |   .2341757   .2713973     0.86   0.392    -.3109417    .7792932
             9  |    .254157   .2741801     0.93   0.358      -.29655     .804864
            10  |  -.1266304   .1334325    -0.95   0.347    -.3946375    .1413767
            11  |   -.124418   .0497628    -2.50   0.016    -.2243696   -.0244664
            12  |   .2844718   .2035075     1.40   0.168    -.1242851    .6932286
            13  |   .2257524   .2040697     1.11   0.274    -.1841337    .6356385
            14  |   .0006597   .1575438     0.00   0.997    -.3157763    .3170957
            15  |   .0186971   .0510898     0.37   0.716    -.0839198    .1213139
            16  |   .0978689   .0452025     2.17   0.035     .0070769    .1886608
            17  |     .08985   .0737439     1.22   0.229     -.058269    .2379689
            18  |  -.0720414   .0113559    -6.34   0.000    -.0948503   -.0492324
            19  |  -.0147217   .0340169    -0.43   0.667    -.0830468    .0536033
            20  |   .1195614   .2063964     0.58   0.565    -.2949981    .5341208
            21  |  -.0025464   .0191249    -0.13   0.895    -.0409599     .035867
            22  |   .0751944   .0603013     1.25   0.218    -.0459243    .1963131
            23  |   .0336116   .1256517     0.27   0.790    -.2187673    .2859904
            24  |   .0992482   .0220412     4.50   0.000     .0549771    .1435193
            25  |   .0609399   .0640011     0.95   0.346    -.0676101      .18949
            26  |   .0406437   .0356114     1.14   0.259    -.0308838    .1121712
            27  |   .2655216   .2303717     1.15   0.255    -.1971936    .7282368
            28  |   .1361276   .1322982     1.03   0.308    -.1296012    .4018564
            29  |   .1236468   .2293051     0.54   0.592    -.3369259    .5842196
            30  |   .1519101   .2064824     0.74   0.465    -.2628219    .5666422
            31  |   -.027394   .0948521    -0.29   0.774    -.2179101    .1631221
            32  |   .1835232   .1577132     1.16   0.250    -.1332532    .5002995
            33  |  -.0788346   .2198103    -0.36   0.721    -.5203365    .3626674
            34  |   -.126025   .0602335    -2.09   0.042    -.2470076   -.0050423
            35  |   .3208145   .2577455     1.24   0.219    -.1968825    .8385116
            36  |  -.0607001   .1487683    -0.41   0.685      -.35951    .2381099
            37  |   .0517614   .0406744     1.27   0.209    -.0299355    .1334583
            38  |   .1349929   .0587149     2.30   0.026     .0170606    .2529252
            39  |  -.0954894   .1618643    -0.59   0.558    -.4206033    .2296246
            40  |   .2237635   .2026986     1.10   0.275    -.1833686    .6308955
            41  |  -.0770363   .0313604    -2.46   0.018    -.1400255   -.0140471
            42  |   .2873621    .251905     1.14   0.259    -.2186039    .7933281
            43  |  -.0058725   .0236656    -0.25   0.805    -.0534063    .0416613
            44  |  -.1434691   .1907433    -0.75   0.455    -.5265884    .2396501
            45  |   .1914897   .1401842     1.37   0.178    -.0900786     .473058
            46  |   .1618153   .2920851     0.55   0.582    -.4248549    .7484855
            47  |  -.0581806   .0490891    -1.19   0.242     -.156779    .0404178
            48  |   .0414131   .0249854     1.66   0.104    -.0087716    .0915977
            49  |   .0747415   .0996857     0.75   0.457    -.1254831    .2749661
            50  |          0  (omitted)
            51  |    .372637   .3096689     1.20   0.235    -.2493514    .9946254
                |
          _cons |   .1332194   2.295567     0.06   0.954    -4.477563    4.744001
---------------------------------------------------------------------------------

. margins, dydx(dividend) at(educ=(0(1)7)) post

Average marginal effects                               Number of obs = 306,018
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: educ = 0
2._at: educ = 1
3._at: educ = 2
4._at: educ = 3
5._at: educ = 4
6._at: educ = 5
7._at: educ = 6
8._at: educ = 7

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |   .2771449   .0305901     9.06   0.000     .2157028     .338587
          2  |   .2490953   .0298619     8.34   0.000      .189116    .3090746
          3  |   .2210458   .0294288     7.51   0.000     .1619362    .2801553
          4  |   .1929962   .0293042     6.59   0.000      .134137    .2518554
          5  |   .1649467   .0294918     5.59   0.000     .1057106    .2241827
          6  |   .1368971   .0299858     4.57   0.000     .0766688    .1971253
          7  |   .1088475   .0307715     3.54   0.001     .0470412    .1706538
          8  |    .080798   .0318272     2.54   0.014     .0168712    .1447248
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist educ if id==2 & year<1984, percent xla(0/7, valuelabel noticks) barw(0.4
> ) xlabel(, angle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-1982") name(educs_graph)

Variables that uniquely identify margins: educ

. 
. ***MT
. eststo edmt: reg voted alaska treatyear i.dividend##c.educ agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id if year<1992, vce(clust
> er id)
note: educ omitted because of collinearity.
note: 1990.year omitted because of collinearity.
note: 2.id omitted because of collinearity.
note: 50.id omitted because of collinearity.

Linear regression                               Number of obs     =    688,941
                                                F(17, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1617
                                                Root MSE          =     .45066

                                       (Std. err. adjusted for 51 clusters in id)
---------------------------------------------------------------------------------
                |               Robust
          voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
         alaska |   .4159145   .1362618     3.05   0.004     .1422247    .6896044
      treatyear |  -.0321507   .0190961    -1.68   0.098    -.0705063    .0062048
     1.dividend |   .0770153   .0128787     5.98   0.000     .0511476    .1028829
           educ |   .0985013   .0020376    48.34   0.000     .0944086    .1025939
                |
dividend#c.educ |
             1  |  -.0150472   .0026703    -5.64   0.000    -.0204106   -.0096838
                |
       agegroup |    .091454   .0009486    96.41   0.000     .0895486    .0933594
           educ |          0  (omitted)
         female |   .0153148   .0024936     6.14   0.000     .0103062    .0203234
                |
          race4 |
         Black  |   .0285963   .0104448     2.74   0.009     .0076172    .0495753
         Asian  |   -.114166    .049277    -2.32   0.025    -.2131417   -.0151902
         Other  |  -.0974988   .0216767    -4.50   0.000    -.1410378   -.0539599
                |
           hisp |  -.0210266   .0135581    -1.55   0.127    -.0482589    .0062057
                |
        empstat |
    Unemployed  |  -.0871533   .0049872   -17.48   0.000    -.0971704   -.0771361
          NILF  |  -.0600702    .002788   -21.55   0.000    -.0656701   -.0544702
                |
          lnpop |   .1259795   .0570379     2.21   0.032     .0114155    .2405434
      lnrgdp_pc |  -.0651955   .0393389    -1.66   0.104    -.1442101    .0138191
           gini |   -.014648   .1423214    -0.10   0.918    -.3005089    .2712128
            edr |   .0357689    .013218     2.71   0.009     .0092198     .062318
                |
           year |
          1980  |   .1356116   .0084136    16.12   0.000     .1187124    .1525109
          1982  |    .053706   .0165118     3.25   0.002     .0205411    .0868708
          1984  |   .1651165   .0138916    11.89   0.000     .1372143    .1930187
          1986  |   .0077779   .0099356     0.78   0.437    -.0121783    .0277341
          1988  |   .1282835   .0091079    14.08   0.000     .1099898    .1465772
          1990  |          0  (omitted)
                |
             id |
             2  |          0  (omitted)
             3  |  -.0315605   .0164299    -1.92   0.060     -.064561      .00144
             4  |   .0523958   .0315138     1.66   0.103    -.0109015    .1156931
             5  |  -.2010072   .1078484    -1.86   0.068    -.4176271    .0156127
             6  |    .046285   .0193818     2.39   0.021     .0073555    .0852145
             7  |   .0685649   .0211609     3.24   0.002     .0260619    .1110679
             8  |   .2201083   .1068412     2.06   0.045     .0055113    .4347053
             9  |   .2239744   .1140703     1.96   0.055    -.0051426    .4530915
            10  |  -.1769192   .0585823    -3.02   0.004    -.2945853   -.0592531
            11  |  -.1392127    .022537    -6.18   0.000    -.1844796   -.0939459
            12  |   .2695387   .0826904     3.26   0.002     .1034502    .4356272
            13  |   .2397731   .0806778     2.97   0.005      .077727    .4018192
            14  |  -.0841197   .0616772    -1.36   0.179    -.2080021    .0397626
            15  |  -.0291176   .0200943    -1.45   0.154    -.0694783    .0112431
            16  |   .0643614    .020218     3.18   0.003     .0237524    .1049704
            17  |   .0729872   .0297836     2.45   0.018      .013165    .1328095
            18  |  -.0741066    .005393   -13.74   0.000    -.0849387   -.0632746
            19  |  -.0006303   .0143411    -0.04   0.965    -.0294352    .0281746
            20  |   .2020825   .0806685     2.51   0.016      .040055    .3641099
            21  |  -.0484781   .0115819    -4.19   0.000    -.0717411   -.0252152
            22  |   .0150293    .026925     0.56   0.579    -.0390512    .0691098
            23  |  -.0654527   .0488212    -1.34   0.186     -.163513    .0326076
            24  |   .1030538   .0089839    11.47   0.000     .0850092    .1210984
            25  |   .0571274   .0266229     2.15   0.037     .0036537    .1106011
            26  |  -.0165845    .014799    -1.12   0.268    -.0463093    .0131403
            27  |   .2910069   .0925401     3.14   0.003     .1051346    .4768792
            28  |   .1406755   .0539499     2.61   0.012     .0323139    .2490371
            29  |   .1116383   .0844765     1.32   0.192    -.0580378    .2813143
            30  |   .1465429   .0790848     1.85   0.070    -.0123035    .3053894
            31  |  -.0929837   .0393662    -2.36   0.022    -.1720531   -.0139143
            32  |   .1535528   .0600416     2.56   0.014     .0329558    .2741499
            33  |  -.1792762   .0870165    -2.06   0.045     -.354054   -.0044984
            34  |  -.1042617    .026332    -3.96   0.000    -.1571511   -.0513723
            35  |   .3565964   .1033408     3.45   0.001     .1490302    .5641626
            36  |  -.1139582   .0580949    -1.96   0.055    -.2306453    .0027289
            37  |   .0166331   .0161246     1.03   0.307    -.0157541    .0490203
            38  |   .1123494   .0230785     4.87   0.000     .0659949     .158704
            39  |  -.1761553   .0629482    -2.80   0.007    -.3025905   -.0497202
            40  |   .2429781   .0802681     3.03   0.004     .0817548    .4042013
            41  |    -.06876   .0109751    -6.27   0.000    -.0908041    -.046716
            42  |   .3255464   .1015936     3.20   0.002     .1214896    .5296031
            43  |  -.0624258   .0099039    -6.30   0.000    -.0823183   -.0425333
            44  |  -.2218929   .0787135    -2.82   0.007    -.3799936   -.0637921
            45  |    .172913   .0526553     3.28   0.002     .0671518    .2786742
            46  |   .2512285   .1146839     2.19   0.033     .0208791    .4815779
            47  |  -.1089192   .0227312    -4.79   0.000    -.1545762   -.0632622
            48  |  -.0147189   .0142753    -1.03   0.307    -.0433917    .0139538
            49  |   .0527919   .0419974     1.26   0.215    -.0315623     .137146
            50  |          0  (omitted)
            51  |   .3320505   .1233982     2.69   0.010     .0841978    .5799031
                |
          _cons |  -1.403429   .9458189    -1.48   0.144    -3.303163    .4963038
---------------------------------------------------------------------------------

. margins, dydx(dividend) at(educ=(0(1)7)) post

Average marginal effects                               Number of obs = 688,941
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: educ = 0
2._at: educ = 1
3._at: educ = 2
4._at: educ = 3
5._at: educ = 4
6._at: educ = 5
7._at: educ = 6
8._at: educ = 7

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |   .0770153   .0128787     5.98   0.000     .0511476    .1028829
          2  |   .0619681   .0116911     5.30   0.000     .0384858    .0854503
          3  |   .0469209   .0110346     4.25   0.000     .0247572    .0690846
          4  |   .0318737   .0110048     2.90   0.006     .0097699    .0539775
          5  |   .0168265   .0116064     1.45   0.153    -.0064857    .0401386
          6  |   .0017793   .0127504     0.14   0.890    -.0238306    .0273892
          7  |  -.0132679   .0143072    -0.93   0.358    -.0420048     .015469
          8  |  -.0283151    .016158    -1.75   0.086    -.0607695    .0041393
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist educ if id==2 & year<1992, percent xla(0/7, valuelabel noticks) barw(0.4
> ) xlabel(, angle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-1990") name(educm_graph)

Variables that uniquely identify margins: educ

. 
. ***LT
. eststo edlt: reg voted alaska treatyear i.dividend##c.educ agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id, vce(cluster id)
note: educ omitted because of collinearity.
note: 2000.year omitted because of collinearity.
note: 2.id omitted because of collinearity.

Linear regression                               Number of obs     =  1,099,013
                                                F(23, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1675
                                                Root MSE          =     .44752

                                       (Std. err. adjusted for 51 clusters in id)
---------------------------------------------------------------------------------
                |               Robust
          voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
         alaska |   .2311013   .0870599     2.65   0.011     .0562364    .4059663
      treatyear |   .0509896   .0185148     2.75   0.008     .0138015    .0881776
     1.dividend |    .095988   .0126299     7.60   0.000       .07062    .1213559
           educ |   .1019864   .0020073    50.81   0.000     .0979547    .1060182
                |
dividend#c.educ |
             1  |   -.019216   .0024225    -7.93   0.000    -.0240816   -.0143503
                |
       agegroup |   .0906411   .0008436   107.44   0.000     .0889467    .0923356
           educ |          0  (omitted)
         female |   .0165936   .0024583     6.75   0.000     .0116558    .0215313
                |
          race4 |
         Black  |   .0282303   .0097225     2.90   0.005     .0087021    .0477584
         Asian  |  -.1612316   .0236505    -6.82   0.000    -.2087352   -.1137281
         Other  |  -.0875973   .0167111    -5.24   0.000    -.1211626    -.054032
                |
           hisp |  -.0296284   .0083022    -3.57   0.001    -.0463039   -.0129529
                |
        empstat |
    Unemployed  |  -.0837549   .0043812   -19.12   0.000    -.0925548    -.074955
          NILF  |  -.0584062   .0024794   -23.56   0.000    -.0633861   -.0534262
                |
          lnpop |   .0551324   .0341224     1.62   0.112    -.0134044    .1236692
      lnrgdp_pc |  -.0555798   .0271064    -2.05   0.046    -.1100247   -.0011349
           gini |   .2736373   .1196404     2.29   0.026     .0333324    .5139422
            edr |  -.0053481   .0167756    -0.32   0.751    -.0390429    .0283467
                |
           year |
          1980  |   .1341772   .0087707    15.30   0.000     .1165607    .1517938
          1982  |  -.0323111   .0173893    -1.86   0.069    -.0672386    .0026164
          1984  |    .077562   .0126524     6.13   0.000     .0521489    .1029751
          1986  |  -.0840911   .0135677    -6.20   0.000    -.1113427   -.0568395
          1988  |   .0273663   .0085725     3.19   0.002     .0101479    .0445847
          1990  |  -.1040516   .0107504    -9.68   0.000    -.1256445   -.0824588
          1992  |   .0580892   .0071213     8.16   0.000     .0437857    .0723927
          1994  |  -.1190798   .0103073   -11.55   0.000    -.1397826    -.098377
          1996  |  -.0234682    .004431    -5.30   0.000    -.0323682   -.0145682
          1998  |  -.1574908   .0084136   -18.72   0.000    -.1743901   -.1405915
          2000  |          0  (omitted)
                |
             id |
             2  |          0  (omitted)
             3  |  -.0644106   .0074605    -8.63   0.000    -.0793954   -.0494257
             4  |  -.0037334   .0186953    -0.20   0.843    -.0412841    .0338172
             5  |  -.0803755   .0641473    -1.25   0.216    -.2092192    .0484682
             6  |   .0165398   .0125301     1.32   0.193    -.0086277    .0417073
             7  |   .0418301   .0162622     2.57   0.013     .0091665    .0744937
             8  |   .0902166   .0648359     1.39   0.170    -.0400103    .2204434
             9  |   .1194907    .077088     1.55   0.127     -.035345    .2743265
            10  |  -.1177658   .0366407    -3.21   0.002    -.1913608   -.0441709
            11  |  -.1124148   .0151973    -7.40   0.000    -.1429396     -.08189
            12  |   .1546088    .050756     3.05   0.004     .0526624    .2565551
            13  |   .1177009   .0475298     2.48   0.017     .0222344    .2131674
            14  |  -.0253815   .0353592    -0.72   0.476    -.0964025    .0456396
            15  |  -.0195746   .0119555    -1.64   0.108     -.043588    .0044388
            16  |   .0437198   .0137974     3.17   0.003     .0160069    .0714326
            17  |   .0273626   .0189012     1.45   0.154    -.0106015    .0653267
            18  |  -.0611753   .0041102   -14.88   0.000    -.0694308   -.0529197
            19  |  -.0029386   .0072065    -0.41   0.685    -.0174133    .0115362
            20  |    .156624   .0446168     3.51   0.001     .0670085    .2462395
            21  |   -.033452   .0079475    -4.21   0.000     -.049415   -.0174889
            22  |    .032708   .0156454     2.09   0.042     .0012834    .0641327
            23  |  -.0039412    .028391    -0.14   0.890    -.0609663    .0530839
            24  |   .1319175   .0198225     6.65   0.000     .0921029    .1717321
            25  |   .0147948   .0159932     0.93   0.359    -.0173285    .0469181
            26  |    .003494   .0086987     0.40   0.690    -.0139778    .0209658
            27  |   .1487322    .056395     2.64   0.011     .0354596    .2620048
            28  |    .057066   .0340478     1.68   0.100     -.011321     .125453
            29  |  -.0066813   .0465129    -0.14   0.886    -.1001053    .0867426
            30  |   .0502648   .0472317     1.06   0.292    -.0446029    .1451325
            31  |  -.0501769   .0227738    -2.20   0.032    -.0959195   -.0044344
            32  |   .0634612    .035333     1.80   0.079    -.0075073    .1344296
            33  |  -.0797249   .0496721    -1.61   0.115    -.1794943    .0200444
            34  |  -.0762347   .0170065    -4.48   0.000    -.1103934   -.0420761
            35  |   .1993468   .0640407     3.11   0.003     .0707172    .3279764
            36  |  -.0403558      .0342    -1.18   0.244    -.1090485    .0283369
            37  |  -.0120179   .0104391    -1.15   0.255    -.0329854    .0089497
            38  |   .0794027   .0137748     5.76   0.000     .0517352    .1070703
            39  |  -.1027403   .0365094    -2.81   0.007    -.1760716    -.029409
            40  |   .1371382   .0489304     2.80   0.007     .0388586    .2354177
            41  |   -.060413   .0056037   -10.78   0.000    -.0716682   -.0491577
            42  |   .1616508   .0624653     2.59   0.013     .0361855    .2871161
            43  |  -.0564004   .0064263    -8.78   0.000     -.069308   -.0434927
            44  |  -.1393183    .046684    -2.98   0.004    -.2330858   -.0455508
            45  |   .0733542   .0299203     2.45   0.018     .0132575    .1334508
            46  |   .1194261   .0685222     1.74   0.088    -.0182048    .2570571
            47  |  -.0760361    .014662    -5.19   0.000    -.1054857   -.0465866
            48  |  -.0047158      .0102    -0.46   0.646    -.0252031    .0157715
            49  |  -.0115077    .026269    -0.44   0.663    -.0642705    .0412551
            50  |   .0553103   .0197778     2.80   0.007     .0155855    .0950351
            51  |   .1691358    .077596     2.18   0.034     .0132796    .3249921
                |
          _cons |  -.5732979   .5421036    -1.06   0.295    -1.662145    .5155492
---------------------------------------------------------------------------------

. margins, dydx(dividend) at(educ=(0(1)7)) post

Average marginal effects                             Number of obs = 1,099,013
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: educ = 0
2._at: educ = 1
3._at: educ = 2
4._at: educ = 3
5._at: educ = 4
6._at: educ = 5
7._at: educ = 6
8._at: educ = 7

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |    .095988   .0126299     7.60   0.000       .07062    .1213559
          2  |    .076772   .0118422     6.48   0.000     .0529862    .1005578
          3  |    .057556   .0115194     5.00   0.000     .0344186    .0806935
          4  |   .0383401   .0117001     3.28   0.002     .0148397    .0618405
          5  |   .0191241   .0123623     1.55   0.128    -.0057063    .0439545
          6  |  -.0000918   .0134349    -0.01   0.995    -.0270765    .0268929
          7  |  -.0193078   .0148291    -1.30   0.199    -.0490929    .0104773
          8  |  -.0385238   .0164634    -2.34   0.023    -.0715915    -.005456
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist educ if id==2, percent xla(0/7, valuelabel noticks) barw(0.4) xlabel(, a
> ngle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-2000")name(educl_graph)

Variables that uniquely identify margins: educ

. 
. esttab edst edmt edlt using Table7.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "R2")) onecell nogaps varwidth(14) modelwidth(6) varlabels(_cons
>  Constant) label title("Heterogenous Effects - Educational Attainment") mlabels("1978-1982" "1978-1990" "1978-2000" ) nonotes addnotes("Notes: Regression coefficie
> nts shown with robust standard errors in parentheses (standard errors for the fixed effects model are clustered by state). Number of Observations is denoted as N. 
> of Obs. Coefficients for the fixed effects are not reported. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to Table7.rtf)

. 
. 
. 
. ** Figure 2 : Marginal Effect of Dividend on Turnout in Alaska with 95% CI
. 
. graph combine educs_graph educm_graph educl_graph, title("Marginal Effect of Dividend on Turnout in Alaska with 95% CI") rows(1) ycommon scheme(s2mono)

. 
. 
. *-----------------------------------------------------------------------------
. ***                               APPENDIX                                 ***
. *-----------------------------------------------------------------------------
. 
. 
. 
. ** Table A3 : Variable Summary Statistics
. 
. *Alaska 
. sum voted age i.race5 female hisp i.empstat educ if id==2

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       voted |     14,099    .6617491    .4731312          0          1
         age |     16,269    38.77847    14.06691         18         99
             |
       race5 |
      White  |     16,269    .8097609    .3925018          0          1
Black/Negro  |     16,269    .0334378    .1797824          0          1
American ..  |     16,269    .0521237    .2222832          0          1
-------------+---------------------------------------------------------
Asian or ..  |     16,269    .0188088    .1358534          0          1
Other (si..  |     16,269    .0858688    .2801789          0          1
             |
      female |     16,269    .5034114    .5000037          0          1
        hisp |     16,107     .020488    .1416668          0          1
             |
     empstat |
Armed For..  |     15,950    .0082759    .0905974          0          1
-------------+---------------------------------------------------------
   Employed  |     15,950    .6717241    .4696005          0          1
 Unemployed  |     15,950    .0596238     .236796          0          1
       NILF  |     15,950    .2603762    .4388536          0          1
             |
        educ |     16,067    4.586046    1.242776          0          7

. tabstat voted age female hisp educ if id==2, statistics(median)

   Stats |     voted       age    female      hisp      educ
---------+--------------------------------------------------
     p50 |         1        36         1         0         4
------------------------------------------------------------

. 
. *All other U.S. States
. sum voted age i.race5 female hisp i.empstat educ if id!=2

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       voted |  1,100,854     .594245    .4910378          0          1
         age |  1,233,968    44.32703    17.91292         18         99
             |
       race5 |
      White  |  1,233,968    .8665452    .3400658          0          1
Black/Negro  |  1,233,968    .0956208    .2940706          0          1
American ..  |  1,233,968    .0044272    .0663896          0          1
-------------+---------------------------------------------------------
Asian or ..  |  1,233,968    .0162346    .1263767          0          1
Other (si..  |  1,233,968    .0171722    .1299129          0          1
             |
      female |  1,233,968    .5303873     .499076          0          1
        hisp |  1,215,097    .0624419    .2419566          0          1
             |
     empstat |
Armed For..  |  1,231,232     .001319    .0362942          0          1
-------------+---------------------------------------------------------
   Employed  |  1,231,232    .6239799    .4843854          0          1
 Unemployed  |  1,231,232    .0369378    .1886092          0          1
       NILF  |  1,231,232    .3377633    .4729476          0          1
             |
        educ |  1,232,207    4.314618    1.374476          0          7

. tabstat voted age female hisp educ if id!=2, statistics(median)

   Stats |     voted       age    female      hisp      educ
---------+--------------------------------------------------
     p50 |         1        41         1         0         4
------------------------------------------------------------

. 
. 
. 
. ** Table A7: Education as a Predictor for Income in Alaska
. 
. *is educ good predictor for inc. in alaska? --> yes
. eststo pred1: reg faminc i.alaska##c.educ i.year if year>1980, vce(cluster id)

Linear regression                               Number of obs     =  1,019,813
                                                F(10, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2707
                                                Root MSE          =     214.88

                                     (Std. err. adjusted for 51 clusters in id)
-------------------------------------------------------------------------------
              |               Robust
       faminc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
     1.alaska |   121.9946   8.911985    13.69   0.000     104.0943    139.8948
         educ |     55.847   1.333582    41.88   0.000     53.16843    58.52558
              |
alaska#c.educ |
           1  |  -15.19991   1.358208   -11.19   0.000    -17.92795   -12.47187
              |
         year |
        1984  |   222.5097   2.358247    94.35   0.000      217.773    227.2464
        1986  |   232.2931   3.424432    67.83   0.000     225.4149    239.1713
        1988  |   241.2659    3.73961    64.52   0.000     233.7546    248.7771
        1990  |   273.0146   4.176143    65.37   0.000     264.6266    281.4026
        1992  |   279.8968   4.515465    61.99   0.000     270.8272    288.9664
        1994  |   300.3196   4.296402    69.90   0.000       291.69    308.9492
        1996  |    322.758   3.964935    81.40   0.000     314.7942    330.7218
        1998  |   344.5813   3.970674    86.78   0.000      336.606    352.5567
        2000  |   368.1615   3.949635    93.21   0.000     360.2284    376.0945
              |
        _cons |   113.8828   8.668722    13.14   0.000     96.47114    131.2944
-------------------------------------------------------------------------------

. esttab pred1 using TableA7.rtf, indicate("Year FEs = *year*") replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth(14) 
> modelwidth(6) varlabels(_cons Constant) label title("Education as a Predictor for Income in Alaska") mlabels("1982-2000") nonotes addnotes("Notes: The significance
>  of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA7.rtf)

. 
. 
. 
. ** Table A8: Heterogeneous Treatment Effects, by Race
. 
. eststo race5st: quietly reg voted treatyear alaska i.dividend##i.race5 female hisp i.empstat i.race5 educ lnpop lnrgdp_pc gini edr i.year i.id if year<1984, vce(cl
> uster id)

. quietly margins, dydx (dividend) at(race5=(1 2 5)) post

. est store racest

. 
. eststo race5mt: quietly reg voted treatyear alaska i.dividend##i.race5 female hisp i.empstat i.race5 educ lnpop lnrgdp_pc gini edr i.year i.id if year<1992, vce(cl
> uster id)

. quietly margins, dydx (dividend) at(race5=(1 2 3 4 5)) post

. est store racemt

. 
. eststo race5lt: quietly reg voted treatyear alaska i.dividend##i.race5 female hisp i.empstat i.race5 educ lnpop lnrgdp_pc gini edr i.year i.id, vce(cluster id)

. quietly margins, dydx (dividend) at(race5=(1 2 3 4 5)) post

. est store racelt

. 
. esttab race5st race5mt race5lt using TableA8.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "R2")) onecell nogaps varwidth(14) modelwidth(6) varla
> bels(_cons Constant) label title("Heterogenous Effects") mlabels("S-T" "S-T" "S-T" ) nonotes addnotes("Notes: Regression coefficients shown with robust standard er
> rors in parentheses (standard errors for the fixed effects model are clustered by state). Number of Observations is denoted as N. of Obs. Coefficients for the fixe
> d effects are not reported. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA8.rtf)

. 
. 
. 
. ** Figure A3 : Marginal Effect of Dividend on Turnout with 95% CI, by Race
. 
. coefplot (racest, label(1978-1982)) (racemt, label(1978-1990)) (racelt, label(1978-2000)), scheme(s2mono)  legend(rows(1)) ylabel(1 "White" 2 "Black" 3 "American I
> ndian/Aleut" 4 "Asian/Pacific Islander" 5 "Other") legend (label (1 "1978-1982"))

. 
. 
. graph drop _all

. 
. ** Table A9 : Heterogeneous Treatment Effects, by Age group
. 
. *ST
. eststo agest: reg voted alaska treatyear i.dividend##c.agegroup agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id if year<1984, vce(
> cluster id)
note: agegroup omitted because of collinearity.
note: 1982.year omitted because of collinearity.
note: 2.id omitted because of collinearity.
note: 50.id omitted because of collinearity.

Linear regression                               Number of obs     =    306,018
                                                F(12, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1624
                                                Root MSE          =     .45152

                                           (Std. err. adjusted for 51 clusters in id)
-------------------------------------------------------------------------------------
                    |               Robust
              voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
             alaska |   .4803921   .3370742     1.43   0.160    -.1966413    1.157426
          treatyear |   .0152754   .0094474     1.62   0.112    -.0037003    .0342511
         1.dividend |   .1131031   .0298515     3.79   0.000     .0531446    .1730615
           agegroup |   .0914109   .0010961    83.40   0.000     .0892094    .0936125
                    |
dividend#c.agegroup |
                 1  |   .0147028   .0010747    13.68   0.000     .0125442    .0168613
                    |
           agegroup |          0  (omitted)
               educ |   .0967285    .001999    48.39   0.000     .0927135    .1007436
             female |   .0120992   .0030661     3.95   0.000     .0059407    .0182577
                    |
              race4 |
             Black  |   .0167581   .0110896     1.51   0.137     -.005516    .0390323
             Other  |  -.0884136     .02496    -3.54   0.001    -.1385472     -.03828
                    |
               hisp |   -.019584   .0190078    -1.03   0.308    -.0577624    .0185943
                    |
            empstat |
        Unemployed  |  -.0919257   .0049012   -18.76   0.000      -.10177   -.0820814
              NILF  |  -.0639707   .0033337   -19.19   0.000    -.0706666   -.0572749
                    |
              lnpop |   .0922869   .1441271     0.64   0.525     -.197201    .3817748
          lnrgdp_pc |   -.172932   .0720386    -2.40   0.020    -.3176258   -.0282381
               gini |   .1276237   .2704642     0.47   0.639    -.4156197     .670867
                edr |   .0974437     .03133     3.11   0.003     .0345156    .1603718
                    |
               year |
              1980  |   .1319723   .0098394    13.41   0.000     .1122093    .1517352
              1982  |          0  (omitted)
                    |
                 id |
                 2  |          0  (omitted)
                 3  |    -.02576   .0526306    -0.49   0.627    -.1314716    .0799517
                 4  |   .0440216   .0778241     0.57   0.574    -.1122927    .2003358
                 5  |  -.0831585   .2628812    -0.32   0.753    -.6111711     .444854
                 6  |    .081744   .0484252     1.69   0.098    -.0155208    .1790088
                 7  |   .1201304   .0406625     2.95   0.005     .0384574    .2018035
                 8  |   .2341199   .2714076     0.86   0.392    -.3110183    .7792581
                 9  |   .2542026   .2741928     0.93   0.358    -.2965298    .8049351
                10  |  -.1265154   .1334341    -0.95   0.348    -.3945258     .141495
                11  |  -.1243715   .0497635    -2.50   0.016    -.2243245   -.0244186
                12  |   .2836059    .203536     1.39   0.170    -.1252082      .69242
                13  |   .2256967   .2040775     1.11   0.274     -.184205    .6355984
                14  |   .0007778   .1575458     0.00   0.996    -.3156622    .3172177
                15  |   .0187315   .0510898     0.37   0.715    -.0838854    .1213484
                16  |   .0978998   .0452063     2.17   0.035     .0071002    .1886994
                17  |   .0898922   .0737492     1.22   0.229    -.0582374    .2380218
                18  |  -.0720364   .0113567    -6.34   0.000     -.094847   -.0492257
                19  |  -.0147016   .0340151    -0.43   0.667    -.0830228    .0536197
                20  |   .1194524   .2064014     0.58   0.565    -.2951169    .5340218
                21  |  -.0024802   .0191259    -0.13   0.897    -.0408956    .0359353
                22  |   .0752845   .0603008     1.25   0.218    -.0458331    .1964022
                23  |   .0336925   .1256533     0.27   0.790    -.2186895    .2860746
                24  |   .0992342   .0220419     4.50   0.000     .0549616    .1435067
                25  |   .0609307   .0640025     0.95   0.346    -.0676221    .1894835
                26  |   .0406944    .035611     1.14   0.259    -.0308324    .1122212
                27  |   .2654243   .2303808     1.15   0.255    -.1973092    .7281578
                28  |   .1361289   .1323043     1.03   0.308    -.1296122      .40187
                29  |   .1236031   .2293148     0.54   0.592    -.3369893    .5841955
                30  |   .1518832    .206491     0.74   0.465    -.2628662    .5666326
                31  |   -.027304   .0948524    -0.29   0.775    -.2178206    .1632127
                32  |   .1834375   .1577225     1.16   0.250    -.1333574    .5002323
                33  |  -.0786855   .2198134    -0.36   0.722    -.5201937    .3628227
                34  |  -.1259983   .0602344    -2.09   0.042    -.2469826   -.0050141
                35  |   .3207086   .2577549     1.24   0.219    -.1970074    .8384246
                36  |   -.060602   .1487705    -0.41   0.685    -.3594164    .2382124
                37  |   .0517519    .040678     1.27   0.209    -.0299523    .1334561
                38  |   .1350154   .0587197     2.30   0.026     .0170735    .2529573
                39  |  -.0953958   .1618672    -0.59   0.558    -.4205156     .229724
                40  |   .2237032   .2027061     1.10   0.275    -.1834439    .6308503
                41  |  -.0770505   .0313611    -2.46   0.018    -.1400411   -.0140598
                42  |   .2872529   .2519136     1.14   0.260    -.2187304    .7932361
                43  |  -.0058619   .0236659    -0.25   0.805    -.0533962    .0416724
                44  |  -.1433345   .1907456    -0.75   0.456    -.5264583    .2397893
                45  |   .1914757   .1401913     1.37   0.178    -.0901069    .4730583
                46  |    .161737   .2920954     0.55   0.582    -.4249538    .7484278
                47  |  -.0581139   .0490893    -1.18   0.242    -.1567127    .0404848
                48  |   .0414468   .0249857     1.66   0.103    -.0087385    .0916321
                49  |   .0746655   .0996886     0.75   0.457    -.1255651     .274896
                50  |          0  (omitted)
                51  |   .3725799   .3096818     1.20   0.235    -.2494344    .9945941
                    |
              _cons |   .1351459   2.295589     0.06   0.953    -4.475679    4.745971
-------------------------------------------------------------------------------------

. margins, dydx(dividend) at(agegroup=(1/6)) post

Average marginal effects                               Number of obs = 306,018
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: agegroup = 1
2._at: agegroup = 2
3._at: agegroup = 3
4._at: agegroup = 4
5._at: agegroup = 5
6._at: agegroup = 6

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |   .1278059   .0297459     4.30   0.000     .0680594    .1875523
          2  |   .1425087    .029679     4.80   0.000     .0828967    .2021206
          3  |   .1572115   .0296508     5.30   0.000     .0976561    .2167668
          4  |   .1719143   .0296616     5.80   0.000     .1123372    .2314913
          5  |   .1866171   .0297113     6.28   0.000     .1269402    .2462939
          6  |   .2013198   .0297996     6.76   0.000     .1414655    .2611742
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist agegroup if id==2 & year<1984, percent xla(1/6, valuelabel noticks) barw
> (0.4) xlabel(, angle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-1982") name(ages_graph)

Variables that uniquely identify margins: agegroup

. 
. eststo agemt: reg voted alaska treatyear i.dividend##c.agegroup agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id if year<1992, vce(
> cluster id)
note: agegroup omitted because of collinearity.
note: 1990.year omitted because of collinearity.
note: 2.id omitted because of collinearity.
note: 50.id omitted because of collinearity.

Linear regression                               Number of obs     =    688,941
                                                F(17, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1617
                                                Root MSE          =     .45066

                                           (Std. err. adjusted for 51 clusters in id)
-------------------------------------------------------------------------------------
                    |               Robust
              voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
             alaska |   .4141378   .1366734     3.03   0.004     .1396212    .6886544
          treatyear |  -.0315362   .0191759    -1.64   0.106    -.0700522    .0069797
         1.dividend |  -.0177713   .0118427    -1.50   0.140     -.041558    .0060155
           agegroup |   .0913616   .0009536    95.81   0.000     .0894463    .0932769
                    |
dividend#c.agegroup |
                 1  |   .0094059   .0011178     8.42   0.000     .0071609     .011651
                    |
           agegroup |          0  (omitted)
               educ |   .0983531   .0020238    48.60   0.000     .0942882    .1024179
             female |   .0153171   .0024929     6.14   0.000     .0103098    .0203243
                    |
              race4 |
             Black  |   .0285111     .01045     2.73   0.009     .0075215    .0495006
             Asian  |  -.1138812    .049367    -2.31   0.025    -.2130377   -.0147246
             Other  |  -.0964828   .0219975    -4.39   0.000    -.1406662   -.0522995
                    |
               hisp |  -.0211425   .0135569    -1.56   0.125    -.0483722    .0060873
                    |
            empstat |
        Unemployed  |   -.087091   .0049876   -17.46   0.000    -.0971089   -.0770732
              NILF  |   -.060003   .0027947   -21.47   0.000    -.0656164   -.0543897
                    |
              lnpop |   .1257326    .057057     2.20   0.032     .0111303     .240335
          lnrgdp_pc |  -.0640422   .0396993    -1.61   0.113    -.1437805    .0156962
               gini |  -.0225648   .1443061    -0.16   0.876    -.3124123    .2672826
                edr |   .0355905   .0132241     2.69   0.010      .009029     .062152
                    |
               year |
              1980  |   .1357353   .0084206    16.12   0.000      .118822    .1526486
              1982  |   .0533396   .0165197     3.23   0.002     .0201589    .0865204
              1984  |     .16473   .0139383    11.82   0.000     .1367341    .1927259
              1986  |   .0074285   .0099999     0.74   0.461    -.0126569    .0275139
              1988  |   .1281345   .0091337    14.03   0.000      .109789    .1464799
              1990  |          0  (omitted)
                    |
                 id |
                 2  |          0  (omitted)
                 3  |    -.03163   .0164307    -1.93   0.060     -.064632    .0013719
                 4  |   .0524405   .0314931     1.67   0.102    -.0108152    .1156962
                 5  |   -.200714   .1078525    -1.86   0.069    -.4173421     .015914
                 6  |   .0461115   .0194148     2.38   0.021     .0071158    .0851073
                 7  |   .0682203    .021258     3.21   0.002     .0255224    .1109182
                 8  |   .2191602   .1070045     2.05   0.046     .0042353     .434085
                 9  |   .2225032   .1144256     1.94   0.057    -.0073273    .4523337
                10  |  -.1764378     .05865    -3.01   0.004    -.2942398   -.0586358
                11  |  -.1391686   .0225342    -6.18   0.000    -.1844298   -.0939073
                12  |   .2682563    .082967     3.23   0.002     .1016123    .4349003
                13  |   .2396174   .0806651     2.97   0.005     .0775969     .401638
                14  |  -.0840961   .0616597    -1.36   0.179    -.2079431     .039751
                15  |  -.0292351   .0200816    -1.46   0.152    -.0695703       .0111
                16  |   .0642339   .0202346     3.17   0.003     .0235915    .1048762
                17  |   .0728276   .0298007     2.44   0.018     .0129711    .1326841
                18  |  -.0741508    .005399   -13.73   0.000     -.084995   -.0633065
                19  |   -.000762   .0143542    -0.05   0.958    -.0295934    .0280694
                20  |   .2018459   .0806728     2.50   0.016     .0398098     .363882
                21  |  -.0487027     .01162    -4.19   0.000    -.0720422   -.0253632
                22  |   .0147532   .0269281     0.55   0.586    -.0393335    .0688398
                23  |  -.0655181   .0487973    -1.34   0.185    -.1635303     .032494
                24  |   .1030164   .0089857    11.46   0.000     .0849681    .1210648
                25  |   .0574024   .0265968     2.16   0.036     .0039812    .1108236
                26  |  -.0166251   .0147946    -1.12   0.266    -.0463409    .0130907
                27  |   .2909783   .0924968     3.15   0.003      .105193    .4767637
                28  |   .1405407   .0539449     2.61   0.012     .0321892    .2488923
                29  |   .1110777   .0845546     1.31   0.195    -.0587552    .2809105
                30  |   .1459323   .0791758     1.84   0.071     -.013097    .3049616
                31  |  -.0931564   .0393471    -2.37   0.022    -.1721874   -.0141254
                32  |   .1533229   .0600483     2.55   0.014     .0327124    .2739334
                33  |  -.1791665   .0870015    -2.06   0.045    -.3539142   -.0044188
                34  |  -.1043637   .0263141    -3.97   0.000    -.1572171   -.0515103
                35  |   .3563196    .103338     3.45   0.001     .1487592      .56388
                36  |  -.1140367   .0580642    -1.96   0.055    -.2306621    .0025887
                37  |   .0166296    .016105     1.03   0.307    -.0157182    .0489775
                38  |   .1121901   .0231011     4.86   0.000     .0657902      .15859
                39  |  -.1760781   .0629362    -2.80   0.007    -.3024892    -.049667
                40  |   .2424254    .080342     3.02   0.004     .0810538    .4037971
                41  |   -.068888   .0109979    -6.26   0.000     -.090978    -.046798
                42  |   .3256727   .1015218     3.21   0.002       .12176    .5295853
                43  |  -.0623995   .0099042    -6.30   0.000    -.0822927   -.0425063
                44  |  -.2214773   .0787488    -2.81   0.007    -.3796489   -.0633057
                45  |   .1726544   .0526794     3.28   0.002     .0668447    .2784641
                46  |   .2506208    .114746     2.18   0.034     .0201468    .4810949
                47  |  -.1091097   .0227209    -4.80   0.000     -.154746   -.0634733
                48  |  -.0150429    .014346    -1.05   0.299    -.0438577     .013772
                49  |   .0524603   .0420393     1.25   0.218    -.0319782    .1368988
                50  |          0  (omitted)
                51  |   .3310727   .1235568     2.68   0.010     .0829016    .5792438
                    |
              _cons |  -1.406933   .9453976    -1.49   0.143     -3.30582     .491954
-------------------------------------------------------------------------------------

. margins, dydx(dividend) at(agegroup=(1/6)) post

Average marginal effects                               Number of obs = 688,941
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: agegroup = 1
2._at: agegroup = 2
3._at: agegroup = 3
4._at: agegroup = 4
5._at: agegroup = 5
6._at: agegroup = 6

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |  -.0083653   .0119212    -0.70   0.486    -.0323097     .015579
          2  |   .0010406   .0121028     0.09   0.932    -.0232685    .0253498
          3  |   .0104466    .012383     0.84   0.403    -.0144255    .0353186
          4  |   .0198525   .0127554     1.56   0.126    -.0057675    .0454725
          5  |   .0292584   .0132121     2.21   0.031     .0027211    .0557957
          6  |   .0386644   .0137447     2.81   0.007     .0110572    .0662715
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist agegroup if id==2 & year<1992, percent xla(1/6, valuelabel noticks) barw
> (0.4) xlabel(, angle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-1990") name(agem_graph)

Variables that uniquely identify margins: agegroup

. 
. eststo agelt: reg voted alaska treatyear i.dividend##c.agegroup agegroup educ female i.race4 hisp i.empstat lnpop lnrgdp_pc gini edr i.year i.id, vce(cluster id)
note: agegroup omitted because of collinearity.
note: 2000.year omitted because of collinearity.
note: 2.id omitted because of collinearity.

Linear regression                               Number of obs     =  1,099,013
                                                F(23, 50)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1674
                                                Root MSE          =     .44752

                                           (Std. err. adjusted for 51 clusters in id)
-------------------------------------------------------------------------------------
                    |               Robust
              voted | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
             alaska |   .2291842   .0873635     2.62   0.012     .0537093     .404659
          treatyear |   .0508437   .0184962     2.75   0.008      .013693    .0879944
         1.dividend |    .022161   .0112465     1.97   0.054    -.0004283    .0447503
           agegroup |   .0906545   .0008486   106.82   0.000       .08895     .092359
                    |
dividend#c.agegroup |
                 1  |   -.005018   .0012357    -4.06   0.000       -.0075    -.002536
                    |
           agegroup |          0  (omitted)
               educ |   .1018169   .0019987    50.94   0.000     .0978023    .1058314
             female |   .0165809   .0024566     6.75   0.000     .0116468     .021515
                    |
              race4 |
             Black  |   .0281625   .0097268     2.90   0.006     .0086256    .0476994
             Asian  |  -.1609644   .0237536    -6.78   0.000    -.2086748   -.1132539
             Other  |  -.0862362   .0172082    -5.01   0.000    -.1207998   -.0516725
                    |
               hisp |  -.0297393   .0083087    -3.58   0.001    -.0464279   -.0130507
                    |
            empstat |
        Unemployed  |  -.0837008   .0043757   -19.13   0.000    -.0924896   -.0749121
              NILF  |  -.0584147   .0024779   -23.57   0.000    -.0633918   -.0534376
                    |
              lnpop |   .0549681   .0341234     1.61   0.114    -.0135708     .123507
          lnrgdp_pc |   -.054286   .0275376    -1.97   0.054    -.1095969    .0010249
               gini |   .2717947   .1204764     2.26   0.028     .0298107    .5137787
                edr |  -.0052263   .0169039    -0.31   0.758    -.0391788    .0287261
                    |
               year |
              1980  |   .1342392   .0087756    15.30   0.000      .116613    .1518655
              1982  |  -.0320366   .0173816    -1.84   0.071    -.0669485    .0028754
              1984  |   .0777638   .0126027     6.17   0.000     .0524505    .1030771
              1986  |  -.0839552   .0135591    -6.19   0.000    -.1111894   -.0567211
              1988  |   .0275162   .0085452     3.22   0.002     .0103527    .0446797
              1990  |  -.1038603   .0107536    -9.66   0.000    -.1254595   -.0822612
              1992  |   .0582735   .0071165     8.19   0.000     .0439795    .0725675
              1994  |  -.1189656   .0103122   -11.54   0.000    -.1396782    -.098253
              1996  |  -.0233457   .0044317    -5.27   0.000     -.032247   -.0144443
              1998  |   -.157468   .0084165   -18.71   0.000    -.1743731   -.1405629
              2000  |          0  (omitted)
                    |
                 id |
                 2  |          0  (omitted)
                 3  |  -.0645426   .0074788    -8.63   0.000    -.0795642   -.0495211
                 4  |   -.003771   .0186893    -0.20   0.841    -.0413096    .0337676
                 5  |  -.0803938   .0641292    -1.25   0.216     -.209201    .0484134
                 6  |   .0162243   .0125891     1.29   0.203    -.0090617    .0415104
                 7  |   .0413254   .0163581     2.53   0.015     .0084691    .0741817
                 8  |   .0893226   .0649455     1.38   0.175    -.0411243    .2197694
                 9  |   .1177556   .0773697     1.52   0.134     -.037646    .2731571
                10  |  -.1175812   .0366533    -3.21   0.002    -.1912016   -.0439608
                11  |  -.1125321   .0151939    -7.41   0.000    -.1430499   -.0820143
                12  |   .1533839   .0509377     3.01   0.004     .0510724    .2556953
                13  |   .1174675   .0475385     2.47   0.017     .0219835    .2129514
                14  |  -.0255415   .0353487    -0.72   0.473    -.0965414    .0454584
                15  |  -.0197142   .0119663    -1.65   0.106    -.0437493     .004321
                16  |   .0434907   .0138319     3.14   0.003     .0157085     .071273
                17  |    .027112   .0189288     1.43   0.158    -.0109075    .0651316
                18  |  -.0612812   .0041277   -14.85   0.000    -.0695718   -.0529905
                19  |  -.0032263   .0072295    -0.45   0.657    -.0177471    .0112945
                20  |   .1562685   .0447046     3.50   0.001     .0664766    .2460604
                21  |  -.0336702   .0080084    -4.20   0.000    -.0497556   -.0175848
                22  |   .0323694   .0156923     2.06   0.044     .0008505    .0638884
                23  |  -.0040484   .0283847    -0.14   0.887    -.0610606    .0529639
                24  |   .1314896   .0199851     6.58   0.000     .0913483    .1716309
                25  |    .014932    .016001     0.93   0.355     -.017207    .0470709
                26  |   .0033633   .0087077     0.39   0.701    -.0141266    .0208532
                27  |   .1485406   .0563824     2.63   0.011     .0352931    .2617881
                28  |   .0567386   .0340643     1.67   0.102    -.0116817    .1251588
                29  |  -.0072617   .0465565    -0.16   0.877    -.1007732    .0862499
                30  |   .0498083    .047283     1.05   0.297    -.0451624     .144779
                31  |  -.0504854   .0227884    -2.22   0.031    -.0962573   -.0047134
                32  |   .0631306   .0353437     1.79   0.080    -.0078592    .1341205
                33  |  -.0798937   .0496542    -1.61   0.114     -.179627    .0198396
                34  |   -.076374   .0170107    -4.49   0.000     -.110541   -.0422071
                35  |   .1989454   .0640459     3.11   0.003     .0703054    .3275854
                36  |  -.0404408   .0341917    -1.18   0.242    -.1091168    .0282351
                37  |  -.0121878   .0104357    -1.17   0.248    -.0331484    .0087728
                38  |   .0792054   .0138025     5.74   0.000     .0514823    .1069284
                39  |    -.10274   .0364994    -2.81   0.007    -.1760512   -.0294289
                40  |   .1367358   .0489587     2.79   0.007     .0383995    .2350722
                41  |  -.0604629   .0056119   -10.77   0.000    -.0717347   -.0491912
                42  |   .1613544   .0624512     2.58   0.013     .0359174    .2867913
                43  |  -.0564941   .0064248    -8.79   0.000    -.0693987   -.0435895
                44  |  -.1393113   .0466728    -2.98   0.004    -.2330565   -.0455662
                45  |   .0732016   .0299269     2.45   0.018     .0130917    .1333115
                46  |    .119035   .0685367     1.74   0.089    -.0186249     .256695
                47  |  -.0762337   .0146826    -5.19   0.000    -.1057246   -.0467428
                48  |  -.0050499   .0102901    -0.49   0.626    -.0257182    .0156183
                49  |  -.0116086   .0262709    -0.44   0.660    -.0643753    .0411581
                50  |   .0550123   .0199125     2.76   0.008     .0150168    .0950079
                51  |   .1682376   .0776689     2.17   0.035      .012235    .3242401
                    |
              _cons |  -.5825472   .5425107    -1.07   0.288    -1.672212    .5071176
-------------------------------------------------------------------------------------

. margins, dydx(dividend) at(agegroup=(1/6)) post

Average marginal effects                             Number of obs = 1,099,013
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  1.dividend
1._at: agegroup = 1
2._at: agegroup = 2
3._at: agegroup = 3
4._at: agegroup = 4
5._at: agegroup = 5
6._at: agegroup = 6

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
0.dividend   |  (base outcome)
-------------+----------------------------------------------------------------
1.dividend   |
         _at |
          1  |    .017143   .0118134     1.45   0.153    -.0065849    .0408709
          2  |    .012125   .0124772     0.97   0.336    -.0129362    .0371863
          3  |   .0071071   .0132235     0.54   0.593    -.0194531    .0336672
          4  |   .0020891    .014039     0.15   0.882    -.0261091    .0302873
          5  |  -.0029289   .0149124    -0.20   0.845    -.0328814    .0270237
          6  |  -.0079468   .0158342    -0.50   0.618    -.0397508    .0238571
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recastci(rline) ciopts(lpattern(dash)) recast(line) legend(off) addplot( hist agegroup if id==2, percent xla(1/6, valuelabel noticks) barw(0.4) xlabel
> (, angle(45)) mfcolor(none) fcolor(none) lcolor(gs10) yaxis(2) yscale(alt axis(2))) scheme(s2mono) title("1978-2000") name(agel_graph)

Variables that uniquely identify margins: agegroup

. 
. 
. esttab agest agemt agelt using TableA9.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "R2")) onecell nogaps varwidth(14) modelwidth(6) varlabels(_
> cons Constant) label title("Heterogenous Effects") mlabels("S-T" "S-T" "S-T" ) nonotes addnotes("Notes: Regression coefficients shown with robust standard errors i
> n parentheses (standard errors for the fixed effects model are clustered by state). Number of Observations is denoted as N. of Obs. Coefficients for the fixed effe
> cts are not reported. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA9.rtf)

. 
. graph combine ages_graph agem_graph agel_graph, title("Marginal Effect of Dividend on Turnout in Alaska with 95% CI, by Age", size(medium)) rows(1) ycommon scheme(
> s2mono)

. 
. 
. 
. ** Table A10 : See Table 3 
. 
. ** Table A11 : Generalized DiD, Individual-Level Data 
. 
. eststo GDD1: quietly reg voted i.alaska##c.div1000 i.year i.id agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr if year<1984, vce(cluster id)

. eststo GDD2: quietly reg voted i.alaska##c.div1000 i.year i.id agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr if year<1992, vce(cluster id)

. eststo GDD3: quietly reg voted i.alaska##c.div1000 i.year i.id agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr, vce(cluster id)

. **post 1982
. eststo GDD4: quietly reg voted i.alaska##c.div1000 i.year i.id agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr if year>1980 & year<1992, vce(c
> luster id)

. eststo GDD5: quietly reg voted i.alaska##c.div1000 i.year i.id agegroup female i.race4 hisp i.empstat educ lnpop lnrgdp_pc gini edr if year>1980, vce(cluster id)

. 
. 
. esttab GDD1 GDD2 GDD3 GDD4 GDD5 using TableA11.rtf, replace b(%9.3f) se(%9.3f) stats(N r2, labels("N. of Obs." "Within R2")) onecell nogaps varwidth(14) modelwidth
> (6) varlabels(_cons Constant) label title("Generalized DiD Fixed-Effects Model with clustered standard errors") mlabels("Short-Term 1978-1982" "Medium-Term 1978-19
> 90" "Long-Term 1978-2000" "Post-Introduction 1982-1990" "Post-Introduction 1982-2000") nonotes addnotes("Notes: Regression coefficients shown with robust standard 
> errors in parentheses that are clustered by state. Not in labor force is denoted as NILF. Number of Observations is denoted as N. of Obs. Dividend in USD / 1000 is
>  the dividend payment in 2016 dollars. The significance of the estimation coefficients is reported as ***p<0.01, **p<0.05, *p<0.1.")
(output written to TableA11.rtf)

. 
. 
. 
. 
end of do-file

. do "/Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/replication_tablea2_dividendpayments.do"

. 
. *-----------------------------------------------------------------------------
. **                       Does a UBI affect voter turnout                    **
. **                             Replication File                             **
. **                       Table A2 : Dividend Payments                       **
. *-----------------------------------------------------------------------------
. 
. use "data_tablea2_dividendpayments.dta", clear

. 
. ** Table A2 : Dividend Payments **
. 
. tabstat dividend_nominal dividend_real, by(year) 

Summary statistics: Mean
Group variable: year (year)

    year |  divi~nal  divi~eal
---------+--------------------
    1982 |      1000   2395.93
    1983 |    386.15    887.29
    1984 |    331.29    730.82
    1985 |       494   1053.59
    1986 |    556.26   1165.97
    1987 |    708.19   1435.06
    1988 |    826.93   1617.25
    1989 |    873.16   1636.13
    1990 |    952.63   1701.16
    1991 |    931.34   1604.76
    1992 |    915.84   1539.76
    1993 |    949.46   1557.03
    1994 |     983.9    1580.5
    1995 |     990.3   1553.36
    1996 |   1130.68   1727.55
    1997 |   1296.54   1939.05
    1998 |   1540.88   2273.68
    1999 |   1769.84   2557.08
    2000 |   1963.86   2744.28
---------+--------------------
   Total |  979.0132  1668.434
------------------------------

. 
end of do-file

. log close
      name:  <unnamed>
       log:  /Users/hannahloffler/Library/Mobile Documents/com~apple~CloudDocs/Alaska/Submission/PSRM/Replication/log_replication_ubiturnout.log
  log type:  text
 closed on:  29 May 2022, 15:30:19
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
